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inproceedings | tarpomanova-etal-2014-noun | Noun-Verb Derivation in the {B}ulgarian and the {R}omanian {W}ord{N}et {--} A Comparative Approach | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.4/ | Tarpomanova, Ekaterina and Leseva, Svetlozara and Todorova, Maria and Dimitrova, Tsvetana and Rizov, Borislav and Barbu Mititelu, Verginica and Irimia, Elena | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 23--31 | Romanian and Bulgarian are Balkan languages with rich derivational morphology that, if introduced into their respective wordnets, can aid broadening of the wordnet content and the possible NLP applications. In this paper we present a joint work on introducing derivation into the Bulgarian and the Romanian WordNets, BulNet and RoWordNet, respectively, by identifying and subsequently labelling the derivationally and semantically related noun-verb pairs. Our research aims at providing a framework for a comparative study on derivation in the two languages and offering training material for the automatic identification and assignment of derivational and morphosemantic relations needed in various applications. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,743 |
inproceedings | majchrakova-etal-2014-semi | Semi-Automatic Detection of Multiword Expressions in the {S}lovak Dependency Treebank | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.5/ | Majchrakova, Daniela and Dusek, Ondrej and Hajic, Jan and Karcova, Agata and Garabik, Radovan | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 32--39 | We describe a method for semi-automatic extraction of Slovak multiword expressions (MWEs) from a dependency treebank. The process uses an automatic conversion from dependency syntactic trees to deep syntax and automatic tagging of verbal argument nodes based on a valency dictionary. Both the valency dictionary and the treebank conversion were adapted from the corresponding Czech versions; the automatically translated valency dictionary has been manually proofread and corrected. There are two main achievements {--} a valency dictionary of Slovak MWEs with direct links to corresponding expressions in the Czech dictionary, PDT-Vallex, and a method of extraction of MWEs from the Slovak Dependency Treebank. The extraction reached very high precision but lower recall in a manual evaluation. This is a work in progress, the overall goal of which is twofold: to create a Slovak language valency dictionary paralleling the Czech one, with bilingual links; and to use the extracted verbal frames in a collocation dictionary of Slovak verbs. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,744 |
inproceedings | stoyanova-2014-automatic | Automatic Categorisation of Multiword Expressions and Named Entities in {B}ulgarian | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.6/ | Stoyanova, Ivelina | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 40--48 | This paper describes an approach for automatic categorisation of various types of multiword expressions (MWEs) with a focus on multiword named entities (MNEs), which compose a large portion of MWEs in general. The proposed algorithm is based on a refined classification of MWEs according to their idiomaticity. While MWE categorisation can be considered as a separate and independent task, it complements the general task of MWE recognition. After outlining the method, we set up an experiment to demonstrate its performance. We use the corpus Wiki1000+ that comprises 6,311 annotated Wikipedia articles of 1,000 or more words each, amounting to 13.4 million words in total. The study also employs a large dictionary of 59,369 MWEs noun phrases (out of more than 85,000 MWEs), labelled with their respective types. The dictionary is compiled automatically and verified semi-automatically. The research presented here is based on Bulgarian although most of the ideas, the methodology and the analysis are applicable to other Slavic and possibly other European languages. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,745 |
inproceedings | derzhanski-siruk-2014-temporal | Temporal Adverbs and Adverbial Expressions in a Corpus of {B}ulgarian and {U}krainian Parallel Texts | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.7/ | Derzhanski, Ivan and Siruk, Olena | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 49--54 | This paper presents a comparative bilingual corpus-based study of the use of several frequent temporal adverbs and adverbial expressions ({\textquoteleft}always', {\textquoteleft}sometimes', {\textquoteleft}never' and their synonyms) in Bulgarian and Ukrainian. The Ukrainian items were selected with the aid of synonym dictionaries of words and of set expressions, the corpus was used to identify their most common Bulgarian counterparts, and the frequencies of the correspondences were compared and scrutinised for possibly informative regularities. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,746 |
inproceedings | dimitrova-boyadzhiev-2014-historical | Historical Corpora of {B}ulgarian Language and Second Position Markers | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.8/ | Dimitrova, Tsvetana and Boyadzhiev, Andrej | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 55--63 | This paper demonstrates how historical corpora can be used in researching language phenomena. We exemplify the advantages and disadvantages through exploring three of the available corpora that contain textual sources of Old and Middle Bulgarian language to shed light on some aspects of the development of two words of ambiguous class. We discuss their behaviour to outline certain conditions for diachronic change they have undergone. The three corpora are accessible online (and offline {--} for downloading search results, xml files, etc.). | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,747 |
inproceedings | jackov-2014-machine | M{\cyra}chine Translation Based on {W}ord{N}et and Dependency Relations | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.9/ | Jackov, Luchezar | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 64--72 | The proposed machine translation (MT) approach uses WordNet (Fellbaum, 1998) as a base for concepts. It identifies the concepts and dependency relations using context-free grammars (CFGs) enriched with features, role markers and dependency markers. Multiple interpretation hypotheses are generated and then are scored using a knowledge base for the dependency relations. The hypothesis with the best score is used for generating the translation. The approach has already been implemented in an MT system for seven languages, namely Bulgarian, English, French, Spanish, Italian, German, and Turkish, and also for Chinese on experimental level. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,748 |
inproceedings | pais-etal-2014-recognize | Recognize the Generality Relation between Sentences Using Asymmetric Association Measures | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.10/ | Pais, Sebastiao and Dias, Gael and Moraliyski, Rumen | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 73--81 | In this paper we focus on a particular case of entailment, namely entailment by generality. We argue that there exist various types of implication, a range of different levels of entailment reasoning, based on lexical, syntactic, logical and common sense clues, at different levels of difficulty. We introduce the paradigm of Textual Entailment (TE) by Generality, which can be defined as the entailment from a specific statement towards a relatively more general statement. In this context, the Text T entails the Hypothesis H, and at the same time H is more general than T . We propose an unsupervised and language-independent method to recognize TE by Generality given a case of Text {\ensuremath{-}} Hypothesis or T {\ensuremath{-}} H where entailment relation holds. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,749 |
inproceedings | pais-etal-2014-unsupervised | Unsupervised and Language Independent Method to Recognize Textual Entailment by Generality | null | sep | 2014 | Sofia, Bulgaria | Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences | https://aclanthology.org/2014.clib-1.11/ | Pais, Sebastiao and Dias, Gael and Cordeiro, Joao and Moraliyski, Rumen | Proceedings of the First International Conference on Computational Linguistics in Bulgaria (CLIB 2014) | 82--90 | In this work we introduce a particular case of textual entailment (TE), namely Textual Entailment by Generality (TEG). In text, there are different kinds of entailment yielded from different types of implicative reasoning (lexical, syntactic, common sense based), but here we focus just on TEG, which can be defined as an entailment from a specific statement towards a relatively more G general one. Therefore, we have T (G){\textrightarrow} H whenever the premise T entails the hypothesis H, the hypothesis being more general than the premise. We propose an unsupervised and language-independent method to recognize TEGs, given a pair T, H in an entailment relation. We have evaluated our proposal G {\textrightarrow} H English pairs, where we know through two experiments: (a) Test on T (G){\textrightarrow} H English pairs, where we know that TEG holds; (b) Test on T {\textrightarrow} H Portuguese pairs, randomly selected with 60{\%} of TEGs and 40{\%} of TE without generality dependency (TEnG). | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,750 |
inproceedings | siahbani-sarkar-2014-expressive | Expressive hierarchical rule extraction for left-to-right translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.1/ | Siahbani, Maryam and Sarkar, Anoop | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 1--14 | Left-to-right (LR) decoding Watanabe et al. (2006) is a promising decoding algorithm for hierarchical phrase-based translation (Hiero) that visits input spans in arbitrary order producing the output translation in left to right order. This leads to far fewer language model calls. But the constrained SCFG grammar used in LR-Hiero (GNF) with at most two non-terminals is unable to account for some complex phrasal reordering. Allowing more non-terminals in the rules results in a more expressive grammar. LR-decoding can be used to decode with SCFGs with more than two non-terminals, but the CKY decoders used for Hiero systems cannot deal with such expressive grammars due to a blowup in computational complexity. In this paper we present a dynamic programming algorithm for GNF rule extraction which efficiently extracts sentence level SCFG rule sets with an arbitrary number of non-terminals. We analyze the performance of the obtained grammar for statistical machine translation on three language pairs. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,751 |
inproceedings | sankaran-sarkar-2014-bayesian | {B}ayesian iterative-cascade framework for hierarchical phrase-based translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.2/ | Sankaran, Baskaran and Sarkar, Anoop | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 15--27 | The typical training of a hierarchical phrase-based machine translation involves a pipeline of multiple steps where mistakes in early steps of the pipeline are propagated without any scope for rectifying them. Additionally the alignments are trained independent of and without being informed of the end goal and hence are not optimized for translation. We introduce a novel Bayesian iterative-cascade framework for training Hiero-style model that learns the alignments together with the synchronous translation grammar in an iterative setting. Our framework addresses the above mentioned issues and provides an elegant and principled alternative to the existing training pipeline. Based on the validation experiments involving two language pairs, our proposed iterative-cascade framework shows consistent gains over the traditional training pipeline for hierarchical translation. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,752 |
inproceedings | stewart-etal-2014-coarse | Coarse {\textquotedblleft}split and lump{\textquotedblright} bilingual language models for richer source information in {SMT} | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.3/ | Stewart, Darlene and Kuhn, Roland and Joanis, Eric and Foster, George | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 28--41 | Recently, there has been interest in automatically generated word classes for improving statistical machine translation (SMT) quality: e.g, (Wuebker et al, 2013). We create new models by replacing words with word classes in features applied during decoding; we call these {\textquotedblleft}coarse models{\textquotedblright}. We find that coarse versions of the bilingual language models (biLMs) of (Niehues et al, 2011) yield larger BLEU gains than the original biLMs. BiLMs provide phrase-based systems with rich contextual information from the source sentence; because they have a large number of types, they suffer from data sparsity. Niehues et al (2011) mitigated this problem by replacing source or target words with parts of speech (POSs). We vary their approach in two ways: by clustering words on the source or target side over a range of granularities (word clustering), and by clustering the bilingual units that make up biLMs (bitoken clustering). We find that loglinear combinations of the resulting coarse biLMs with each other and with coarse LMs (LMs based on word classes) yield even higher scores than single coarse models. When we add an appealing {\textquotedblleft}generic{\textquotedblright} coarse configuration chosen on English {\ensuremath{>}} French devtest data to four language pairs (keeping the structure fixed, but providing language-pair-specific models for each pair), BLEU gains on blind test data against strong baselines averaged over 5 runs are +0.80 for English {\ensuremath{>}} French, +0.35 for French {\ensuremath{>}} English, +1.0 for Arabic {\ensuremath{>}} English, and +0.6 for Chinese {\ensuremath{>}} English. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,753 |
inproceedings | ortega-etal-2014-using | Using any machine translation source for fuzzy-match repair in a computer-aided translation setting | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.4/ | Ortega, John E. and S{\'a}nchez-Martinez, Felipe and Forcada, Mikel L. | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 42--53 | When a computer-assisted translation (CAT) tool does not find an exact match for the source segment to translate in its translation memory (TM), translators must use fuzzy matches that come from translation units in the translation memory that do not completely match the source segment. We explore the use of a fuzzy-match repair technique called patching to repair translation proposals from a TM in a CAT environment using any available machine translation system, or any external bilingual source, regardless of its internals. Patching attempts to aid CAT tool users by repairing fuzzy matches and proposing improved translations. Our results show that patching improves the quality of translation proposals and reduces the amount of edit operations to perform, especially when a specific set of restrictions is applied. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,754 |
inproceedings | arcan-etal-2014-enhancing | Enhancing statistical machine translation with bilingual terminology in a {CAT} environment | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.5/ | Arcan, Mihael and Turchi, Marco and Topelli, Sara and Buitelaar, Paul | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 54--68 | In this paper, we address the problem of extracting and integrating bilingual terminology into a Statistical Machine Translation (SMT) system for a Computer Aided Translation (CAT) tool scenario. We develop a framework that, taking as input a small amount of parallel in-domain data, gathers domain-specific bilingual terms and injects them in an SMT system to enhance the translation productivity. Therefore, we investigate several strategies to extract and align bilingual terminology, and to embed it into the SMT. We compare two embedding methods that can be easily used at run-time without altering the normal activity of an SMT system: XML markup and the cache-based model. We tested our framework on two different domains showing improvements up to 15{\%} BLEU score points. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,755 |
inproceedings | simard-2014-clean | Clean data for training statistical {MT}: the case of {MT} contamination | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.6/ | Simard, Michel | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 69--82 | Users of Statistical Machine Translation (SMT) sometimes turn to the Web to obtain data to train their systems. One problem with this approach is the potential for {\textquotedblleft}MT contamination{\textquotedblright}: when large amounts of parallel data are collected automatically, there is a risk that a non-negligible portion consists of machine-translated text. Theoretically, using this kind of data to train SMT systems is likely to reinforce the errors committed by other systems, or even by an earlier versions of the same system. In this paper, we study the effect of MT-contaminated training data on SMT quality, by performing controlled simulations under a wide range of conditions. Our experiments highlight situations in which MT contamination can be harmful, and assess the potential of decontamination techniques. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,756 |
inproceedings | flanagan-2014-bilingual | Bilingual phrase-to-phrase alignment for arbitrarily-small datasets | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.7/ | Flanagan, Kevin | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 83--95 | This paper presents a novel system for sub-sentential alignment of bilingual sentence pairs, however few, using readily-available machine-readable bilingual dictionaries. Performance is evaluated against an existing gold-standard parallel corpus where word alignments are annotated, showing results that are a considerable improvement on a comparable system and on GIZA++ performance for the same corpus. Since na{\"ive application of the system for N languages would require N(N - 1) dictionaries, it is also evaluated using a pivot language, where only 2(N - 1) dictionaries would be required, with surprisingly similar performance. The system is proposed as an alternative to statistical methods, for use with very small corpora or for {\textquotelefton-the-fly' alignment. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,757 |
inproceedings | zhang-etal-2014-probabilistic | A probabilistic feature-based fill-up for {SMT} | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.8/ | Zhang, Jian and Li, Liangyou and Way, Andy and Liu, Qun | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 96--109 | In this paper, we describe an effective translation model combination approach based on the estimation of a probabilistic Support Vector Machine (SVM). We collect domain knowledge from both in-domain and general-domain corpora inspired by a commonly used data selection algorithm, which we then use as features for the SVM training. Drawing on previous work on binary-featured phrase table fill-up (Nakov, 2008; Bisazza et al., 2011), we substitute the binary feature in the original work with our probabilistic domain-likeness feature. Later, we design two experiments to evaluate the proposed probabilistic feature-based approach on the French-to-English language pair using data provided at WMT07, WMT13 and IWLST11 translation tasks. Our experiments demonstrate that translation performance can gain significant improvements of up to +0.36 and +0.82 BLEU scores by using our probabilistic feature-based translation model fill-up approach compared with the binary featured fill-up approach in both experiments. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,758 |
inproceedings | ding-etal-2014-document | Document-level re-ranking with soft lexical and semantic features for statistical machine translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.9/ | Ding, Chenchen and Utiyama, Masao and Sumita, Eiichiro | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 110--123 | We introduce two document-level features to polish baseline sentence-level translations generated by a state-of-the-art statistical machine translation (SMT) system. One feature uses the word-embedding technique to model the relation between a sentence and its context on the target side; the other feature is a crisp document-level token-type ratio of target-side translations for source-side words to model the lexical consistency in translation. The weights of introduced features are tuned to optimize the sentence- and document-level metrics simultaneously on the basis of Pareto optimality. Experimental results on two different schemes with different corpora illustrate that the proposed approach can efficiently and stably integrate document-level information into a sentence-level SMT system. The best improvements were approximately 0.5 BLEU on test sets with statistical significance. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,759 |
inproceedings | chen-etal-2014-comparison | A comparison of mixture and vector space techniques for translation model adaptation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.10/ | Chen, Boxing and Kuhn, Roland and Foster, George | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 124--138 | In this paper, we propose two extensions to the vector space model (VSM) adaptation technique (Chen et al., 2013b) for statistical machine translation (SMT), both of which result in significant improvements. We also systematically compare the VSM techniques to three mixture model adaptation techniques: linear mixture, log-linear mixture (Foster and Kuhn, 2007), and provenance features (Chiang et al., 2011). Experiments on NIST Chinese-to-English and Arabic-to-English tasks show that all methods achieve significant improvement over a competitive non-adaptive baseline. Except for the original VSM adaptation method, all methods yield improvements in the +1.7-2.0 BLEU range. Combining them gives further significant improvements of up to +2.6-3.3 BLEU over the baseline. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,760 |
inproceedings | hasler-etal-2014-combining | Combining domain and topic adaptation for {SMT} | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.11/ | Hasler, Eva and Haddow, Barry and Koehn, Philipp | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 139--151 | Recent years have seen increased interest in adapting translation models to test domains that are known in advance as well as using latent topic representations to adapt to unknown test domains. However, the relationship between domains and latent topics is still somewhat unclear and topic adaptation approaches typically do not make use of domain knowledge in the training data. We show empirically that combining domain and topic adaptation approaches can be beneficial and that topic representations can be used to predict the domain of a test document. Our best combined model yields gains of up to 0.82 BLEU over a domain-adapted translation system and up to 1.67 BLEU over an unadapted system, measured on the stronger of two training conditions. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,761 |
inproceedings | mathur-etal-2014-online | Online multi-user adaptive statistical machine translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.12/ | Mathur, Prashant and Cettolo, Mauro and Federico, Marcello and de Souza, Jos{\'e} G.C. | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 152--165 | In this paper we investigate the problem of adapting a machine translation system to the feedback provided by multiple post-editors. It is well know that translators might have very different post-editing styles and that this variability hinders the application of online learning methods, which indeed assume a homogeneous source of adaptation data. We hence propose multi-task learning to leverage bias information from each single post-editors in order to constrain the evolution of the SMT system. A new framework for significance testing with sentence level metrics is described which shows that Multi-Task learning approaches outperforms existing online learning approaches, with significant gains of 1.24 and 1.88 TER score over a strong online adaptive baseline, on a test set of post-edits produced by four translators texts and on a popular benchmark with multiple references, respectively. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,762 |
inproceedings | cettolo-etal-2014-repetition | The repetition rate of text as a predictor of the effectiveness of machine translation adaptation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.13/ | Cettolo, Mauro and Bertoldi, Nicola and Federico, Marcello | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 166--179 | Since the effectiveness of MT adaptation relies on the text repetitiveness, the question on how to measure repetitions in a text naturally arises. This work deals with the issue of looking for and evaluating text features that might help the prediction of the impact of MT adaptation on translation quality. In particular, the repetition rate metric, we recently proposed, is compared to other features employed in very related NLP tasks. The comparison is carried out through a regression analysis between feature values and MT performance gains by dynamically adapted versus non-adapted MT engines, on five different translation tasks. The main outcome of experiments is that the repetition rate correlates better than any other considered feature with the MT gains yielded by the online adaptation, although using all features jointly results in better predictions than with any single feature. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,763 |
inproceedings | aydin-ozgur-2014-expanding | Expanding machine translation training data with an out-of-domain corpus using language modeling based vocabulary saturation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.14/ | Ayd{\in, Burak and {\"Ozg{\"ur, Arzucan | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 180--192 | The training data size is of utmost importance for statistical machine translation (SMT), since it affects the training time, model size, decoding speed, as well as the system`s overall success. One of the challenges for developing SMT systems for languages with less resources is the limited sizes of the available training data. In this paper, we propose an approach for expanding the training data by including parallel texts from an out-of-domain corpus. Selecting the best out-of-domain sentences for inclusion in the training set is important for the overall performance of the system. Our method is based on first ranking the out-of-domain sentences using a language modeling approach, and then, including the sentences to the training set by using the vocabulary saturation filter technique. We evaluated our approach for the English-Turkish language pair and obtained promising results. Performance improvements of up to +0.8 BLEU points for the English-Turkish translation system are achieved. We compared our results with the translation model combination approaches as well and reported the improvements. Moreover, we implemented our system with dependency parse tree based language modeling in addition to the n-gram based language modeling and reported comparable results. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,764 |
inproceedings | wuebker-etal-2014-comparison | Comparison of data selection techniques for the translation of video lectures | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.15/ | Wuebker, Joern and Ney, Hermann and Mart{\'i}nez-Villaronga, Adri{\`a} and Gim{\'e}nez, Adri{\`a} and Juan, Alfons and Servan, Christophe and Dymetman, Marc and Mirkin, Shachar | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 193--207 | For the task of online translation of scientific video lectures, using huge models is not possible. In order to get smaller and efficient models, we perform data selection. In this paper, we perform a qualitative and quantitative comparison of several data selection techniques, based on cross-entropy and infrequent n-gram criteria. In terms of BLEU, a combination of translation and language model cross-entropy achieves the most stable results. As another important criterion for measuring translation quality in our application, we identify the number of out-of-vocabulary words. Here, infrequent n-gram recovery shows superior performance. Finally, we combine the two selection techniques in order to benefit from both their strengths. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,765 |
inproceedings | yang-etal-2014-review | Review and analysis of {C}hina workshop on machine translation 2013 evaluation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.16/ | Yang, Sitong and Yu, Heng and Zhao, Hongmei and Liu, Qun and L{\"u, Yajuan | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 208--221 | This paper gives a general review and detailed analysis of China Workshop on Machine Translation (CWMT) Evaluation. Compared with the past CWMT evaluation campaigns, CWMT2013 evaluation is characterized as follows: first, adopting gray-box evaluation which makes the results more replicable and controllable; second, adding one rule-based system as a counterpart; third, carrying out manual evaluations on some specific tasks to give a more comprehensive analysis of the translation errors. Boosted by those new features, our analysis and case study on the evaluation results shows the pros and cons of both rule-based and statistical systems, and reveals some interesting correlations bewteen automatic and manual evaluation metrics on different translation systems. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,766 |
inproceedings | niehues-etal-2014-combining | Combining techniques from different {NN}-based language models for machine translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.17/ | Niehues, Jan and Allauzen, Alexander and Yvon, Fran{\c{c}}ois and Waibel, Alex | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 222--233 | This paper presents two improvements of language models based on Restricted Boltzmann Machine (RBM) for large machine translation tasks. In contrast to other continuous space approach, RBM based models can easily be integrated into the decoder and are able to directly learn a hidden representation of the n-gram. Previous work on RBM-based language models do not use a shared word representation and therefore, they might suffer of a lack of generalization for larger contexts. Moreover, since the training step is very time consuming, they are only used for quite small copora. In this work we add a shared word representation for the RBM-based language model by factorizing the weight matrix. In addition, we propose an efficient and tailored sampling algorithm that allows us to drastically speed up the training process. Experiments are carried out on two German to English translation tasks and the results show that the training time could be reduced by a factor of 10 without any drop in performance. Furthermore, the RBM-based model can also be trained on large size corpora. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,767 |
inproceedings | sudoh-etal-2014-japanese | {J}apanese-to-{E}nglish patent translation system based on domain-adapted word segmentation and post-ordering | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.18/ | Sudoh, Katsuhito and Nagata, Masaaki and Mori, Shinsuke and Kawahara, Tatsuya | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 234--248 | This paper presents a Japanese-to-English statistical machine translation system specialized for patent translation. Patents are practically useful technical documents, but their translation needs different efforts from general-purpose translation. There are two important problems in the Japanese-to-English patent translation: long distance reordering and lexical translation of many domain-specific terms. We integrated novel lexical translation of domain-specific terms with a syntax-based post-ordering framework that divides the machine translation problem into lexical translation and reordering explicitly for efficient syntax-based translation. The proposed lexical translation consists of a domain-adapted word segmentation and an unknown word transliteration. Experimental results show our system achieves better translation accuracy in BLEU and TER compared to the baseline methods. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,768 |
inproceedings | li-etal-2014-discriminative | A discriminative framework of integrating translation memory features into {SMT} | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.19/ | Li, Liangyou and Way, Andy and Liu, Qun | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 249--260 | Combining Translation Memory (TM) with Statistical Machine Translation (SMT) together has been demonstrated to be beneficial. In this paper, we present a discriminative framework which can integrate TM into SMT by incorporating TM-related feature functions. Experiments on English{--}Chinese and English{--}French tasks show that our system using TM feature functions only from the best fuzzy match performs significantly better than the baseline phrase- based system on both tasks, and our discriminative model achieves comparable results to those of an effective generative model which uses similar features. Furthermore, with the capacity of handling a large amount of features in the discriminative framework, we propose a method to efficiently use multiple fuzzy matches which brings more feature functions and further significantly improves our system. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,769 |
inproceedings | ruiz-federico-2014-assessing | Assessing the impact of speech recognition errors on machine translation quality | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.20/ | Ruiz, Nicholas and Federico, Marcello | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 261--274 | In spoken language translation, it is crucial that an automatic speech recognition (ASR) system produces outputs that can be adequately translated by a statistical machine translation (SMT) system. While word error rate (WER) is the standard metric of ASR quality, the assumption that each ASR error type is weighted equally is violated in a SMT system that relies on structured input. In this paper, we outline a statistical framework for analyzing the impact of specific ASR error types on translation quality in a speech translation pipeline. Our approach is based on linear mixed-effects models, which allow the analysis of ASR errors on a translation quality metric. The mixed-effects models take into account the variability of ASR systems and the difficulty of each speech utterance being translated in a specific experimental setting. We use mixed-effects models to verify that the ASR errors that compose the WER metric do not contribute equally to translation quality and that interactions exist between ASR errors that cumulatively affect a SMT system`s ability to translate an utterance. Our experiments are carried out on the English to French language pair using eight ASR systems and seven post-edited machine translation references from the IWSLT 2013 evaluation campaign. We report significant findings that demonstrate differences in the contributions of specific ASR error types toward speech translation quality and suggest further error types that may contribute to translation difficulty. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,770 |
inproceedings | weller-etal-2014-using | Using noun class information to model selectional preferences for translating prepositions in {SMT} | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.21/ | Weller, Marion and Schulte im Walde, Sabine and Fraser, Alexander | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 275--287 | Translating prepositions is a difficult and under-studied problem in SMT. We present a novel method to improve the translation of prepositions by using noun classes to model their selectional preferences. We compare three variants of noun class information: (i) classes induced from the lexical resource GermaNet or obtained from clusterings based on either (ii) window information or (iii) syntactic features. Furthermore, we experiment with PP rule generalization. While we do not significantly improve over the baseline, our results demonstrate that (i) integrating selectional preferences as rigid class annotation in the parse tree is sub-optimal, and that (ii) clusterings based on window co-occurrence are more robust than syntax-based clusters or GermaNet classes for the task of modeling selectional preferences. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,771 |
inproceedings | specia-shah-2014-predicting | Predicting human translation quality | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.22/ | Specia, Lucia and Shah, Kashif | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 288--300 | We present a first attempt at predicting the quality of translations produced by human, professional translators. We examine datasets annotated for quality at sentence- and word-level for four language pairs and provide experiments with prediction models for these datasets. We compare the performance of such models against that of models built from machine translations, highlighting a number of challenges in estimating quality and detecting errors in human translations. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,772 |
inproceedings | mirkin-besacier-2014-data | Data selection for compact adapted {SMT} models | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.23/ | Mirkin, Shachar and Besacier, Laurent | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 301--314 | Data selection is a common technique for adapting statistical translation models for a specific domain, which has been shown to both improve translation quality and to reduce model size. Selection relies on some in-domain data, of the same domain of the texts expected to be translated. Selecting the sentence-pairs that are most similar to the in-domain data from a pool of parallel texts has been shown to be effective; yet, this approach holds the risk of resulting in a limited coverage, when necessary n-grams that do appear in the pool are less similar to in-domain data that is available in advance. Some methods select additional data based on the actual text that needs to be translated. While useful, this is not always a practical scenario. In this work we describe an extensive exploration of data selection techniques over Arabic to French datasets, and propose methods to address both similarity and coverage considerations while maintaining a limited model size. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,773 |
inproceedings | dholakia-sarkar-2014-pivot | Pivot-based triangulation for low-resource languages | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.24/ | Dholakia, Rohit and Sarkar, Anoop | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 315--328 | This paper conducts a comprehensive study on the use of triangulation for four very low-resource languages: Mawukakan and Maninkakan, Haitian Kreyol and Malagasy. To the best of our knowledge, ours is the first effective translation system for the first two of these languages. We improve translation quality by adding data using pivot languages and exper- imentally compare previously proposed triangulation design options. Furthermore, since the low-resource language pair and pivot language pair data typically come from very different domains, we use insights from domain adaptation to tune the weighted mixture of direct and pivot based phrase pairs to improve translation quality. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,774 |
inproceedings | may-etal-2014-arabizi | An {A}rabizi-{E}nglish social media statistical machine translation system | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.25/ | May, Jonathan and Benjira, Yassine and Echihabi, Abdessamad | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 329--341 | We present a machine translation engine that can translate romanized Arabic, often known as Arabizi, into English. With such a system we can, for the first time, translate the massive amounts of Arabizi that are generated every day in the social media sphere but until now have been uninterpretable by automated means. We accomplish our task by leveraging a machine translation system trained on non-Arabizi social media data and a weighted finite-state transducer-based Arabizi-to-Arabic conversion module, equipped with an Arabic character-based n-gram language model. The resulting system allows high capacity on-the-fly translation from Arabizi to English. We demonstrate via several experiments that our performance is quite close to the theoretical maximum attained by perfect deromanization of Arabizi input. This constitutes the first presentation of a high capacity end-to-end social media Arabizi-to-English translation system. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,775 |
inproceedings | mansour-etal-2014-automatic | Automatic dialect classification for statistical machine translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.26/ | Mansour, Saab and Al-Onaizan, Yaser and Blackwood, Graeme and Tillmann, Christoph | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 342--355 | The training data for statistical machine translation are gathered from various sources representing a mixture of domains. In this work, we argue that when translating dialects representing varieties of the same language, a manually assigned data source is not a reliable indicator of the dialect. We resort to automatic dialect classification to refine the training corpora according to the different dialects and build improved dialect specific systems. A fairly standard classifier for Arabic developed within this work achieves state-of-the-art performance, with classification precision above 90{\%}, making it usefully accurate for our application. The classification of the data is then used to distinguish between the different dialects, split the data accordingly, and utilize the new splits for several adaptation techniques. Performing translation experiments on a large scale dialectal Arabic to English translation task, our results show that the classifier generates better contrast between the dialects and achieves superior translation quality than using the original manual corpora splits. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,776 |
inproceedings | guo-etal-2014-tunable | A tunable language model for statistical machine translation | Al-Onaizan, Yaser and Simard, Michel | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-researchers.27/ | Guo, Junfei and Liu, Juan and Han, Qi and Maletti, Andreas | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas: MT Researchers Track | 356--368 | A novel variation of modified KNESER-NEY model using monomial discounting is presented and integrated into the MOSES statistical machine translation toolkit. The language model is trained on a large training set as usual, but its new discount parameters are tuned to the small development set. An in-domain and cross-domain evaluation of the language model is performed based on perplexity, in which sizable improvements are obtained. Additionally, the performance of the language model is also evaluated in several major machine translation tasks including Chinese-to-English. In those tests, the test data is from a (slightly) different domain than the training data. The experimental results indicate that the new model significantly outperforms a baseline model using SRILM in those domain adaptation scenarios. The new language model is thus ideally suited for domain adaptation without sacrificing performance on in-domain experiments. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,777 |
inproceedings | alabau-etal-2014-integrating | Integrating online and active learning in a computer-assisted translation workbench | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.1/ | Alabau, Vicent and Gonz{\'a}lez-Rubio, Jes{\'u}s and Ortiz-Mart{\'i}nez, Daniel and Sanchis-Trilles, Germ{\'a}n and Casacuberta, Francisco and Garc{\'i}a-Mart{\'i}nez, Mercedes and Mesa-Lao, Bartolom{\'e} and Petersen, Dan Cheung and Dragsted, Barbara and Carl, Michael | Workshop on interactive and adaptive machine translation | 1--8 | This paper describes a pilot study with a computed-assisted translation workbench aiming at testing the integration of online and active learning features. We investigate the effect of these features on translation productivity, using interactive translation prediction (ITP) as a baseline. User activity data were collected from five beta testers using key-logging and eye-tracking. User feedback was also collected at the end of the experiments in the form of retrospective think-aloud protocols. We found that OL performs better than ITP, especially in terms of translation speed. In addition, AL provides better translation quality than ITP for the same levels of user effort. We plan to incorporate these features in the final version of the workbench. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,799 |
inproceedings | de-souza-etal-2014-towards | Towards a combination of online and multitask learning for {MT} quality estimation: a preliminary study | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.2/ | de Souza, Jos{\'e} G.C. and Turchi, Marco and Negri, Matteo | Workshop on interactive and adaptive machine translation | 9--19 | Quality estimation (QE) for machine translation has emerged as a promising way to provide real-world applications with methods to estimate at run-time the reliability of automatic translations. Real-world applications, however, pose challenges that go beyond those of current QE evaluation settings. For instance, the heterogeneity and the scarce availability of training data might contribute to significantly raise the bar. To address these issues we compare two alternative machine learning paradigms, namely online and multi-task learning, measuring their capability to overcome the limitations of current batch methods. The results of our experiments, which are carried out in the same experimental setting, demonstrate the effectiveness of the two methods and suggest their complementarity. This indicates, as a promising research avenue, the possibility to combine their strengths into an online multi-task approach to the problem. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,800 |
inproceedings | germann-2014-dynamic | Dynamic phrase tables for machine translation in an interactive post-editing scenario | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.3/ | Germann, Ulrich | Workshop on interactive and adaptive machine translation | 20--31 | This paper presents a phrase table implementation for the Moses system that computes phrase table entries for phrase-based statistical machine translation (PBSMT) on demand by sampling an indexed bitext. While this approach has been used for years in hierarchical phrase-based translation, the PBSMT community has been slow to adopt this paradigm, due to concerns that this would be slow and lead to lower translation quality. The experiments conducted in the course of this work provide evidence to the contrary: without loss in translation quality, the sampling phrase table ranks second out of four in terms of speed, being slightly slower than hash table look-up (Junczys-Dowmunt, 2012) and considerably faster than current implementations of the approach suggested by Zens and Ney (2007). In addition, the underlying parallel corpus can be updated in real time, so that professionally produced translations can be used to improve the quality of the machine translation engine immediately. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,801 |
inproceedings | mathur-cettolo-2014-optimized | Optimized {MT} online learning in computer assisted translation | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.4/ | Mathur, Prashant and Cettolo, Mauro | Workshop on interactive and adaptive machine translation | 32--41 | In this paper we propose a cascading framework for optimizing online learning in machine translation for a computer assisted translation scenario. With the use of online learning, several hyperparameters associated with the learning algorithm are introduced. The number of iterations of online learning can affect the translation quality as well. We discuss these issues and propose a few approaches to optimize the hyperparameters and to find the number of iterations required for online learning. We experimentally show that optimizing hyperparameters and number of iterations in online learning yields consistent improvement against baseline results. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,802 |
inproceedings | seligman-dillinger-2014-behind | Behind the scenes in an interactive speech translation system | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.5/ | Seligman, Mark and Dillinger, Mike | Workshop on interactive and adaptive machine translation | 42--50 | This paper describes the facilities of Converser for Healthcare 4.0, a highly interactive speech translation system which enables users to verify and correct speech recognition and machine translation. Corrections are presently useful for real-time reliability, and in the future should prove applicable to offline machine learning. We provide examples of interactive tools in action, emphasizing semantically controlled back-translation and lexical disambiguation, and explain for the first time the techniques employed in the tools' creation, focusing upon compilation of a database of semantic cues and its connection to third-party MT engines. Planned extensions of our techniques to statistical MT are also discussed. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,803 |
inproceedings | singla-etal-2014-predicting | Predicting post-editor profiles from the translation process | Casacuberta, Francisco and Federico, Marcello and Koehn, Philipp | oct # " 22" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-workshop.6/ | Singla, Karan and Orrego-Carmona, David and Gonzales, Ashleigh Rhea and Carl, Michael and Bangalore, Srinivas | Workshop on interactive and adaptive machine translation | 51--60 | The purpose of the current investigation is to predict post-editor profiles based on user behaviour and demographics using machine learning techniques to gain a better understanding of post-editor styles. Our study extracts process unit features from the CasMaCat LS14 database from the CRITT Translation Process Research Database (TPR-DB). The analysis has two main research goals: We create n-gram models based on user activity and part-of-speech sequences to automatically cluster post-editors, and we use discriminative classifier models to characterize post-editors based on a diverse range of translation process features. The classification and clustering of participants resulting from our study suggest this type of exploration could be used as a tool to develop new translation tool features or customization possibilities. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,804 |
inproceedings | sanchez-gijon-torres-hostench-2014-mt | {MT} post-editing into the mother tongue of into a foreign language? {S}panish-to-{E}nglish {MT} translation output post-edited by translation trainees | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.1/ | S{\'a}nchez-Gij{\'o}n, Pilar and Torres-Hostench, Olga | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 5--19 | The aim of this study is to analyse whether translation trainees who are not native speakers of the target language are able to perform as well as those who are native speakers, and whether they achieve the expected quality in a {\textquotedblleft}good enough{\textquotedblright} post-editing (PE) job. In particular the study focuses on the performance of two groups of students doing PE from Spanish into English: native English speakers and native Spanish speakers. A pilot study was set up to collect evidence to compare and contrast the two groups' performances. Trainees from both groups had been given the same training in PE and were asked to post-edit 30 sentences translated from Spanish to English. The PE output was analyzed taking into account accuracy errors (mistranslations and omissions) as well as language errors (grammatical errors and syntax errors). The results show that some native Spanish speakers corrected just as many errors as the native English speakers. Furthermore, the Spanish-speaking trainees outperformed their English-speaking counterparts when identifying mistranslations and omissions. Moreover, the performances of the best English-speaking and Spanish-speaking trainees at identifying grammar and syntax errors were very similar. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,805 |
inproceedings | aranberri-etal-2014-comparison | Comparison of post-editing productivity between professional translators and lay users | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.2/ | Aranberri, Nora and Labaka, Gorka and Diaz de Ilarraza, Arantza and Sarasola, Kepa | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 20--33 | This work compares the post-editing productivity of professional translators and lay users. We integrate an English to Basque MT system within Bologna Translation Service, an end-to-end translation management platform, and perform a producitivity experiment in a real working environment. Six translators and six lay users translate or post-edit two texts from English into Basque. Results suggest that overall, post-editing increases translation throughput for both translators and users, although the latter seem to benefit more from the MT output. We observe that translators and users perceive MT differently. Additionally, a preliminary analysis seems to suggest that familiarity with the domain, source text complexity and MT quality might affect potential productivity gain. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,806 |
inproceedings | schwartz-2014-monolingual | Monolingual post-editing by a domain expert is highly effective for translation triage | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.3/ | Schwartz, Lane | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 34--44 | Various small-scale pilot studies have found that for at least some documents, monolingual target language speakers may be able to successfully post-edit machine translations. We begin by analyzing previously published post-editing data to ascertain the effect, if any, of original source language on post-editing quality. Schwartz et al. (2014) hypothesized that post-editing success may be more pronounced when the monolingual post-editors are experts in the domain of the translated documents. This work tests that hypothesis by asking a domain expert to post-edit machine translations of a French scientific article (Besacier, 2014) into English. We find that the monolingual domain expert post-editor was able to successfully post-edit 86.7{\%} of the sentences without requesting assistance from a bilingual post-editor. We evaluate the post-edited sentences according to a bilingual adequacy metric, and find that 96.5{\%} of those sentences post-edited by only a monolingual post-editor are judged to be completely correct. These results confirm that a monolingual domain expert can successfully triage the post-editing effort, substantially reducing the workload on the bilingual post-editor by only sending the most challenging sentences to the bilingual post-editor. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,807 |
inproceedings | teixeira-2014-perceived | Perceived vs. measured performance in the post-editing of suggestions from machine translation and translation memories | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.4/ | Teixeira, Carlos S.C. | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 45--59 | This paper investigates the behaviour of ten professional translators when performing translation tasks with and without translation suggestions, and with and without translation metadata. The measured performances are then compared with the translators' perceptions of their performances. The variables that are taken into consideration are time, edits and errors. Keystroke logging and screen recording are used to measure time and edits, an error score system is used to identify errors and post-performance interviews are used to assess participants' perceptions. The study looks at the correlations between the translators' perceptions and their actual performances, and tries to understand the reasons behind any discrepancies. Translators are found to prefer an environment with translation suggestions and translation metadata to an environment without metadata. This preference, however, does not always correlate with an improved performance. Task familiarity seems to be the most prominent factor responsible for the positive perceptions, rather than any intrinsic characteristics in the tasks. A certain prejudice against MT is also present in some of the comments. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,808 |
inproceedings | gaspari-etal-2014-perception | Perception vs. reality: measuring machine translation post-editing productivity | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.5/ | Gaspari, Federico and Toral, Antonio and Naskar, Sudip Kumar and Groves, Declan and Way, Andy | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 60--72 | This paper presents a study of user-perceived vs real machine translation (MT) post-editing effort and productivity gains, focusing on two bidirectional language pairs: English{---}German and English{---}Dutch. Twenty experienced media professionals post-edited statistical MT output and also manually translated comparative texts within a production environment. The paper compares the actual post-editing time against the users' perception of the effort and time required to post-edit the MT output to achieve publishable quality, thus measuring real (vs perceived) productivity gains. Although for all the language pairs users perceived MT post-editing to be slower, in fact it proved to be a faster option than manual translation for two translation directions out of four, i.e. for Dutch to English, and (marginally) for English to German. For further objective scrutiny, the paper also checks the correlation of three state-of-the-art automatic MT evaluation metrics (BLEU, METEOR and TER) with the actual post-editing time. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,809 |
inproceedings | lacruz-etal-2014-cognitive | Cognitive demand and cognitive effort in post-editing | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.6/ | Lacruz, Isabel and Denkowski, Michael and Lavie, Alon | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 73--84 | The pause to word ratio, the number of pauses per word in a post-edited MT segment, is an indicator of cognitive effort in post-editing (Lacruz and Shreve, 2014). We investigate how low the pause threshold can reasonably be taken, and we propose that 300 ms is a good choice, as pioneered by Schilperoord (1996). We then seek to identify a good measure of the cognitive demand imposed by MT output on the post-editor, as opposed to the cognitive effort actually exerted by the post-editor during post-editing. Measuring cognitive demand is closely related to measuring MT utility, the MT quality as perceived by the post-editor. HTER, an extrinsic edit to word ratio that does not necessarily correspond to actual edits per word performed by the post-editor, is a well-established measure of MT quality, but it does not comprehensively capture cognitive demand (Koponen, 2012). We investigate intrinsic measures of MT quality, and so of cognitive demand, through edited-error to word metrics. We find that the transfer-error to word ratio predicts cognitive effort better than mechanical-error to word ratio (Koby and Champe, 2013). We identify specific categories of cognitively challenging MT errors whose error to word ratios correlate well with cognitive effort. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,810 |
inproceedings | killman-2014-vocabulary | Vocabulary accuracy of statistical machine translation in the legal context | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.7/ | Killman, Jeffrey | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 85--98 | This paper examines the accuracy of free online SMT output provided by Google Translate (GT) in the difficult context of legal translation. The paper analyzes English machine translations produced by GT for a large sample of Spanish legal vocabulary items that originate from a voluminous text of judgment summaries produced by the Supreme Court of Spain. Prior to this study, this same text was translated into English but without MT and it was found that the majority of the translation solutions that were chosen for the said vocabulary items could be hand-selected from mostly EU databases with versions in English and Spanish. The paper argues that MT in the legal translation context should be worthwhile if the output can consistently provide a reasonable amount of accurate translations of the types of vocabulary items translators in this context often have to do research on before being able to effectively translate them. Much of the currently available translated text used to train SMT comes from international organizations, such as the EU and the UN which often write about legal matters. Moreover, SMT can use the immediate co-text of vocabulary items as a way of attempting to identify correct translations in its database. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,811 |
inproceedings | moran-etal-2014-towards | Towards desktop-based {CAT} tool instrumentation | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.8/ | Moran, John and Saam, Christian and Lewis, Dave | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 99--112 | Though a number of web-based CAT tools have emerged over recent years, to date the most common form of CAT tool used by translators remains the desktop-based CAT tool. However, currently none of the most commonly used desktop-based CAT tools provide a means of measuring translation speed at a segment level. This metric is important, as previous work on MT productivity testing has shown that edit distance can be a misleading measure of MT post-editing effort. In this paper we present iOmegaT, an instrumented version of a popular desktop-based open-source CAT tool called OmegaT. We survey a number of similar applications and outline some of the weaknesses of web-based CAT tools for experi- enced professional translators. On the basis of a two productivity test carried out using iOmegaT we show why it is important to be able to identify fast good post-editors to maximize MT utility and how this is problematic using only edit-distance measures. Finally, we argue how and why instrumentation could be added to more commonly used desktop-based CAT tools that are paid for by freelance translators if their privacy is respected. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,812 |
inproceedings | ocurran-2014-translation | Translation quality in post-edited versus human-translated segments: a case study | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.9/ | O{'}Curran, Elaine | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 113--118 | We analyze the linguistic quality results for a post-editing productivity test that contains a 3:1 ratio of post-edited segments versus human-translated segments, in order to assess if there is a difference in the final translation quality of each segment type and also to investigate the type of errors that are found in each segment type. Overall, we find that the human-translated segments contain more errors per word than the post-edited segments and although the error categories logged are similar across the two segment types, the most notable difference is that the number of stylistic errors in the human translations is 3 times higher than in the post-edited translations. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,813 |
inproceedings | gorog-2014-taus | {TAUS} post-editing course | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.10/ | G{\"or{\"og, Attila | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 119 | While there is a massive adoption of MT post-editing as a new service in the global translation industry, a common reference to skills and best practices to do this work well has been missing. TAUS took up the challenge to provide a course that would integrate with the DQF tools and the post-editing best practices developed by TAUS members in the previous years and offers both theory and practice to develop post-editing skills. The contribution of language service providers who are involved in MT and post-editing on a daily basis allowed TAUS to deliver fast on this industry need. This online course addresses the challenges for linguists and translators deciding to work on post-editing assignments and is aimed at those who want to learn the best practices and skills to become more efficient and proficient in the activity of post-editing. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,814 |
inproceedings | specia-shah-2014-quest | {Q}u{E}st: A framework for translation quality estimation | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.12/ | Specia, Lucia and Shah, Kashif | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 121 | We present QUEST, an open source framework for translation quality estimation. QUEST provides a wide range of feature extractors from source and translation texts and external resources and tools. These go from simple, language-independent features, to advanced, linguistically motivated features. They include features that rely on information from the translation system and features that are oblivious to the way translations were produced. In addition, it provides wrappers for a well-known machine learning toolkit, scikit-learn, including techniques for feature selection and model building, as well as parameter optimisation. We also present a Web interface and functionalities for non-expert users. Using this interface, quality predictions (or internal features of the framework) can be obtained without the installation of the toolkit and the building of prediction models. The interface also provides a ranking method for multiple translations given for the same source text according to their predicted quality. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,816 |
inproceedings | schwartz-2014-open | An open source desktop post-editing tool | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.13/ | Schwartz, Lane | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 122 | We present a simple user interface for post-editing that presents the user with the source sentence, machine translation, and word alignments for each sentence in a test document (Figure 1). This software is open source, written in Java, and has no external dependencies; it can be run on Linux, Mac OS X, and Windows. This software was originally designed for monolingual post-editors, but should be equally usable by bilingual post-editors. While it may seem counter-intuitive to present monolingual post-editors with the source sentence, we found that the presence of alignment links between source words and target words can in fact aid a monolingual post-editor, especially with regard to correcting word order. For example, in our experiments using this interface (Schwartz et al., 2014), post-editors encountered some sentences where a word or phrase was enclosed within bracketing punctuation marks (such as quotation marks, commas, or parentheses) in the source sentence, and the machine translation system incorrectly reordered the word or phrase outside the enclosing punctuation; by examining the alignment links the post-editors were able to correct such reordering mistakes. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,817 |
inproceedings | denkowski-etal-2014-real-time | Real time adaptive machine translation: cdec and {T}rans{C}enter | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.14/ | Denkowski, Michael and Lavie, Alon and Lacruz, Isabel and Dyer, Chris | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 123 | cdec Realtime and TransCenter provide an end-to-end experimental setup for machine translation post-editing research. Realtime provides a framework for building adaptive MT systems that learn from post-editor feedback while TransCenter incorporates a web-based translation interface that connects users to these systems and logs post-editing activity. This combination allows the straightforward deployment of MT systems specifically for post-editing and analysis of translator productivity when working with adaptive systems. Both toolkits are freely available under open source licenses. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,818 |
inproceedings | kishimoto-etal-2014-post | Post-editing user interface using visualization of a sentence structure | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.15/ | Kishimoto, Yudai and Nakazawa, Toshiaki and Kawahara, Daisuke and Kurohashi, Sadao | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 124 | Translation has become increasingly important by virtue of globalization. To reduce the cost of translation, it is necessary to use machine translation and further to take advantage of post-editing based on the result of a machine translation for accurate information dissemination. Such post-editing (e.g., PET [Aziz et al., 2012]) can be used practically for translation between European languages, which has a high performance in statistical machine translation. However, due to the low accuracy of machine translation between languages with different word order, such as Japanese-English and Japanese-Chinese, post-editing has not been used actively. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,819 |
inproceedings | obrien-etal-2014-kanjingo-mobile | {K}anjingo: a mobile app for post-editing | O'Brien, Sharon and Simard, Michel and Specia, Lucia | oct # " 22-26" | 2014 | Vancouver, Canada | Association for Machine Translation in the Americas | https://aclanthology.org/2014.amta-wptp.16/ | O{'}Brien, Sharon and Moorkens, Joss and Vreeke, Joris | Proceedings of the 11th Conference of the Association for Machine Translation in the Americas | 125--127 | We present Kanjingo, a mobile app for post-editing currently running under iOS. The App was developed using an agile methodoly at CNGL, DCU. Though it could be used for numerous scenarios, our test scenario involved the post-editing of machine translated sample content for the non-profit translation organization Translators without Borders. Feedback from a first round of user testing for English-French and English-Spanish was positive, but users also identified a number of usability issues that required improvement. These issues were addressed in a second development round and a second usability evaluation was carried out in collaboration with another non-profit translation organization, The Rosetta Foundation, again with French and Spanish as target languages. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 68,820 |
article | tackstrom-etal-2013-token | Token and Type Constraints for Cross-Lingual Part-of-Speech Tagging | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1001/ | T{\"ackstr{\"om, Oscar and Das, Dipanjan and Petrov, Slav and McDonald, Ryan and Nivre, Joakim | null | 1--12 | We consider the construction of part-of-speech taggers for resource-poor languages. Recently, manually constructed tag dictionaries from Wiktionary and dictionaries projected via bitext have been used as type constraints to overcome the scarcity of annotated data in this setting. In this paper, we show that additional token constraints can be projected from a resource-rich source language to a resource-poor target language via word-aligned bitext. We present several models to this end; in particular a partially observed conditional random field model, where coupled token and type constraints provide a partial signal for training. Averaged across eight previously studied Indo-European languages, our model achieves a 25{\%} relative error reduction over the prior state of the art. We further present successful results on seven additional languages from different families, empirically demonstrating the applicability of coupled token and type constraints across a diverse set of languages. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00205 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,215 |
article | pitler-etal-2013-finding | Finding Optimal 1-Endpoint-Crossing Trees | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1002/ | Pitler, Emily and Kannan, Sampath and Marcus, Mitchell | null | 13--24 | Dependency parsing algorithms capable of producing the types of crossing dependencies seen in natural language sentences have traditionally been orders of magnitude slower than algorithms for projective trees. For 95.8{--}99.8{\%} of dependency parses in various natural language treebanks, whenever an edge is crossed, the edges that cross it all have a common vertex. The optimal dependency tree that satisfies this 1-Endpoint-Crossing property can be found with an O(n4) parsing algorithm that recursively combines forests over intervals with one exterior point. 1-Endpoint-Crossing trees also have natural connections to linguistics and another class of graphs that has been studied in NLP. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00206 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,216 |
article | regneri-etal-2013-grounding | Grounding Action Descriptions in Videos | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1003/ | Regneri, Michaela and Rohrbach, Marcus and Wetzel, Dominikus and Thater, Stefan and Schiele, Bernt and Pinkal, Manfred | null | 25--36 | Recent work has shown that the integration of visual information into text-based models can substantially improve model predictions, but so far only visual information extracted from static images has been used. In this paper, we consider the problem of grounding sentences describing actions in visual information extracted from videos. We present a general purpose corpus that aligns high quality videos with multiple natural language descriptions of the actions portrayed in the videos, together with an annotation of how similar the action descriptions are to each other. Experimental results demonstrate that a text-based model of similarity between actions improves substantially when combined with visual information from videos depicting the described actions. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00207 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,217 |
article | qian-liu-2013-branch | Branch and Bound Algorithm for Dependency Parsing with Non-local Features | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1004/ | Qian, Xian and Liu, Yang | null | 37--48 | Graph based dependency parsing is inefficient when handling non-local features due to high computational complexity of inference. In this paper, we proposed an exact and efficient decoding algorithm based on the Branch and Bound (B{\&}B) framework where non-local features are bounded by a linear combination of local features. Dynamic programming is used to search the upper bound. Experiments are conducted on English PTB and Chinese CTB datasets. We achieved competitive Unlabeled Attachment Score (UAS) when no additional resources are available: 93.17{\%} for English and 87.25{\%} for Chinese. Parsing speed is 177 words per second for English and 97 words per second for Chinese. Our algorithm is general and can be adapted to non-projective dependency parsing or other graphical models. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00208 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,218 |
article | artzi-zettlemoyer-2013-weakly | Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1005/ | Artzi, Yoav and Zettlemoyer, Luke | null | 49--62 | The context in which language is used provides a strong signal for learning to recover its meaning. In this paper, we show it can be used within a grounded CCG semantic parsing approach that learns a joint model of meaning and context for interpreting and executing natural language instructions, using various types of weak supervision. The joint nature provides crucial benefits by allowing situated cues, such as the set of visible objects, to directly influence learning. It also enables algorithms that learn while executing instructions, for example by trying to replicate human actions. Experiments on a benchmark navigational dataset demonstrate strong performance under differing forms of supervision, including correctly executing 60{\%} more instruction sets relative to the previous state of the art. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00209 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,219 |
article | pate-goldwater-2013-unsupervised | Unsupervised Dependency Parsing with Acoustic Cues | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1006/ | Pate, John K and Goldwater, Sharon | null | 63--74 | Unsupervised parsing is a difficult task that infants readily perform. Progress has been made on this task using text-based models, but few computational approaches have considered how infants might benefit from acoustic cues. This paper explores the hypothesis that word duration can help with learning syntax. We describe how duration information can be incorporated into an unsupervised Bayesian dependency parser whose only other source of information is the words themselves (without punctuation or parts of speech). Our results, evaluated on both adult-directed and child-directed utterances, show that using word duration can improve parse quality relative to words-only baselines. These results support the idea that acoustic cues provide useful evidence about syntactic structure for language-learning infants, and motivate the use of word duration cues in NLP tasks with speech. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00210 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,220 |
article | li-li-2013-novel | A Novel Feature-based {B}ayesian Model for Query Focused Multi-document Summarization | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1008/ | Li, Jiwei and Li, Sujian | null | 89--98 | Supervised learning methods and LDA based topic model have been successfully applied in the field of multi-document summarization. In this paper, we propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic models in a principled way, thus taking advantages of both topic model and feature based supervised learning methods. Experimental results on DUC2007, TAC2008 and TAC2009 demonstrate the effectiveness of our approach. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00212 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,222 |
article | beigman-klebanov-etal-2013-using | Using Pivot-Based Paraphrasing and Sentiment Profiles to Improve a Subjectivity Lexicon for Essay Data | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1009/ | Beigman Klebanov, Beata and Madnani, Nitin and Burstein, Jill | null | 99--110 | We demonstrate a method of improving a seed sentiment lexicon developed on essay data by using a pivot-based paraphrasing system for lexical expansion coupled with sentiment profile enrichment using crowdsourcing. Profile enrichment alone yields up to 15{\%} improvement in the accuracy of the seed lexicon on 3-way sentence-level sentiment polarity classification of essay data. Using lexical expansion in addition to sentiment profiles provides a further 7{\%} improvement in performance. Additional experiments show that the proposed method is also effective with other subjectivity lexicons and in a different domain of application (product reviews). | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00213 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,223 |
article | sangati-keller-2013-incremental | Incremental Tree Substitution Grammar for Parsing and Sentence Prediction | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1010/ | Sangati, Federico and Keller, Frank | null | 111--124 | In this paper, we present the first incremental parser for Tree Substitution Grammar (TSG). A TSG allows arbitrarily large syntactic fragments to be combined into complete trees; we show how constraints (including lexicalization) can be imposed on the shape of the TSG fragments to enable incremental processing. We propose an efficient Earley-based algorithm for incremental TSG parsing and report an F-score competitive with other incremental parsers. In addition to whole-sentence F-score, we also evaluate the partial trees that the parser constructs for sentence prefixes; partial trees play an important role in incremental interpretation, language modeling, and psycholinguistics. Unlike existing parsers, our incremental TSG parser can generate partial trees that include predictions about the upcoming words in a sentence. We show that it outperforms an n-gram model in predicting more than one upcoming word. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00214 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,224 |
article | sahakian-snyder-2013-modeling | Modeling Child Divergences from Adult Grammar | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1011/ | Sahakian, Sam and Snyder, Benjamin | null | 125--138 | During the course of first language acquisition, children produce linguistic forms that do not conform to adult grammar. In this paper, we introduce a data set and approach for systematically modeling this child-adult grammar divergence. Our corpus consists of child sentences with corrected adult forms. We bridge the gap between these forms with a discriminatively reranked noisy channel model that translates child sentences into equivalent adult utterances. Our method outperforms MT and ESL baselines, reducing child error by 20{\%}. Our model allows us to chart specific aspects of grammar development in longitudinal studies of children, and investigate the hypothesis that children share a common developmental path in language acquisition. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00215 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,225 |
article | hayashi-etal-2013-efficient | Efficient Stacked Dependency Parsing by Forest Reranking | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1012/ | Hayashi, Katsuhiko and Kondo, Shuhei and Matsumoto, Yuji | null | 139--150 | This paper proposes a discriminative forest reranking algorithm for dependency parsing that can be seen as a form of efficient stacked parsing. A dynamic programming shift-reduce parser produces a packed derivation forest which is then scored by a discriminative reranker, using the 1-best tree output by the shift-reduce parser as guide features in addition to third-order graph-based features. To improve efficiency and accuracy, this paper also proposes a novel shift-reduce parser that eliminates the spurious ambiguity of arc-standard transition systems. Testing on the English Penn Treebank data, forest reranking gave a state-of-the-art unlabeled dependency accuracy of 93.12. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00216 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,226 |
article | matuschek-gurevych-2013-dijkstra | Dijkstra-{WSA}: A Graph-Based Approach to Word Sense Alignment | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1013/ | Matuschek, Michael and Gurevych, Iryna | null | 151--164 | In this paper, we present Dijkstra-WSA, a novel graph-based algorithm for word sense alignment. We evaluate it on four different pairs of lexical-semantic resources with different characteristics (WordNet-OmegaWiki, WordNet-Wiktionary, GermaNet-Wiktionary and WordNet-Wikipedia) and show that it achieves competitive performance on 3 out of 4 datasets. Dijkstra-WSA outperforms the state of the art on every dataset if it is combined with a back-off based on gloss similarity. We also demonstrate that Dijkstra-WSA is not only flexibly applicable to different resources but also highly parameterizable to optimize for precision or recall. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00217 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,227 |
article | lopez-etal-2013-learning | Learning to translate with products of novices: a suite of open-ended challenge problems for teaching {MT} | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1014/ | Lopez, Adam and Post, Matt and Callison-Burch, Chris and Weese, Jonathan and Ganitkevitch, Juri and Ahmidi, Narges and Buzek, Olivia and Hanson, Leah and Jamil, Beenish and Lee, Matthias and Lin, Ya-Ting and Pao, Henry and Rivera, Fatima and Shahriyari, Leili and Sinha, Debu and Teichert, Adam and Wampler, Stephen and Weinberger, Michael and Xu, Daguang and Yang, Lin and Zhao, Shang | null | 165--178 | Machine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them are best learned by doing. As a centerpiece of our MT course, we devised a series of open-ended challenges for students in which the goal was to improve performance on carefully constrained instances of four key MT tasks: alignment, decoding, evaluation, and reranking. Students brought a diverse set of techniques to the problems, including some novel solutions which performed remarkably well. A surprising and exciting outcome was that student solutions or their combinations fared competitively on some tasks, demonstrating that even newcomers to the field can help improve the state-of-the-art on hard NLP problems while simultaneously learning a great deal. The problems, baseline code, and results are freely available. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00218 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,228 |
article | lewis-steedman-2013-combined | Combined Distributional and Logical Semantics | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1015/ | Lewis, Mike and Steedman, Mark | null | 179--192 | We introduce a new approach to semantics which combines the benefits of distributional and formal logical semantics. Distributional models have been successful in modelling the meanings of content words, but logical semantics is necessary to adequately represent many function words. We follow formal semantics in mapping language to logical representations, but differ in that the relational constants used are induced by offline distributional clustering at the level of predicate-argument structure. Our clustering algorithm is highly scalable, allowing us to run on corpora the size of Gigaword. Different senses of a word are disambiguated based on their induced types. We outperform a variety of existing approaches on a wide-coverage question answering task, and demonstrate the ability to make complex multi-sentence inferences involving quantifiers on the FraCaS suite. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00219 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,229 |
article | krishnamurthy-kollar-2013-jointly | Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1016/ | Krishnamurthy, Jayant and Kollar, Thomas | null | 193--206 | This paper introduces Logical Semantics with Perception (LSP), a model for grounded language acquisition that learns to map natural language statements to their referents in a physical environment. For example, given an image, LSP can map the statement {\textquotedblleft}blue mug on the table{\textquotedblright} to the set of image segments showing blue mugs on tables. LSP learns physical representations for both categorical ({\textquotedblleft}blue,{\textquotedblright} {\textquotedblleft}mug{\textquotedblright}) and relational ({\textquotedblleft}on{\textquotedblright}) language, and also learns to compose these representations to produce the referents of entire statements. We further introduce a weakly supervised training procedure that estimates LSP`s parameters using annotated referents for entire statements, without annotated referents for individual words or the parse structure of the statement. We perform experiments on two applications: scene understanding and geographical question answering. We find that LSP outperforms existing, less expressive models that cannot represent relational language. We further find that weakly supervised training is competitive with fully supervised training while requiring significantly less annotation effort. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00220 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,230 |
article | chang-yih-2013-dual | Dual Coordinate Descent Algorithms for Efficient Large Margin Structured Prediction | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1017/ | Chang, Ming-Wei and Yih, Wen-tau | null | 207--218 | Due to the nature of complex NLP problems, structured prediction algorithms have been important modeling tools for a wide range of tasks. While there exists evidence showing that linear Structural Support Vector Machine (SSVM) algorithm performs better than structured Perceptron, the SSVM algorithm is still less frequently chosen in the NLP community because of its relatively slow training speed. In this paper, we propose a fast and easy-to-implement dual coordinate descent algorithm for SSVMs. Unlike algorithms such as Perceptron and stochastic gradient descent, our method keeps track of dual variables and updates the weight vector more aggressively. As a result, this training process is as efficient as existing online learning methods, and yet derives consistently better models, as evaluated on four benchmark NLP datasets for part-of-speech tagging, named-entity recognition and dependency parsing. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00221 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,231 |
article | lluis-etal-2013-joint | Joint Arc-factored Parsing of Syntactic and Semantic Dependencies | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1018/ | Llu{\'i}s, Xavier and Carreras, Xavier and M{\`a}rquez, Llu{\'i}s | null | 219--230 | In this paper we introduce a joint arc-factored model for syntactic and semantic dependency parsing. The semantic role labeler predicts the full syntactic paths that connect predicates with their arguments. This process is framed as a linear assignment task, which allows to control some well-formedness constraints. For the syntactic part, we define a standard arc-factored dependency model that predicts the full syntactic tree. Finally, we employ dual decomposition techniques to produce consistent syntactic and predicate-argument structures while searching over a large space of syntactic configurations. In experiments on the CoNLL-2009 English benchmark we observe very competitive results. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00222 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,232 |
article | srikumar-roth-2013-modeling | Modeling Semantic Relations Expressed by Prepositions | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1019/ | Srikumar, Vivek and Roth, Dan | null | 231--242 | This paper introduces the problem of predicting semantic relations expressed by prepositions and develops statistical learning models for predicting the relations, their arguments and the semantic types of the arguments. We define an inventory of 32 relations, building on the word sense disambiguation task for prepositions and collapsing related senses across prepositions. Given a preposition in a sentence, our computational task to jointly model the preposition relation and its arguments along with their semantic types, as a way to support the relation prediction. The annotated data, however, only provides labels for the relation label, and not the arguments and types. We address this by presenting two models for preposition relation labeling. Our generalization of latent structure SVM gives close to 90{\%} accuracy on relation labeling. Further, by jointly predicting the relation, arguments, and their types along with preposition sense, we show that we can not only improve the relation accuracy, but also significantly improve sense prediction accuracy. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00223 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,233 |
article | zhai-etal-2013-unsupervised | Unsupervised Tree Induction for Tree-based Translation | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1020/ | Zhai, Feifei and Zhang, Jiajun and Zhou, Yu and Zong, Chengqing | null | 243--254 | In current research, most tree-based translation models are built directly from parse trees. In this study, we go in another direction and build a translation model with an unsupervised tree structure derived from a novel non-parametric Bayesian model. In the model, we utilize synchronous tree substitution grammars (STSG) to capture the bilingual mapping between language pairs. To train the model efficiently, we develop a Gibbs sampler with three novel Gibbs operators. The sampler is capable of exploring the infinite space of tree structures by performing local changes on the tree nodes. Experimental results show that the string-to-tree translation system using our Bayesian tree structures significantly outperforms the strong baseline string-to-tree system using parse trees. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00224 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,234 |
article | sirts-goldwater-2013-minimally | Minimally-Supervised Morphological Segmentation using {A}daptor {G}rammars | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1021/ | Sirts, Kairit and Goldwater, Sharon | null | 255--266 | This paper explores the use of Adaptor Grammars, a nonparametric Bayesian modelling framework, for minimally supervised morphological segmentation. We compare three training methods: unsupervised training, semi-supervised training, and a novel model selection method. In the model selection method, we train unsupervised Adaptor Grammars using an over-articulated metagrammar, then use a small labelled data set to select which potential morph boundaries identified by the metagrammar should be returned in the final output. We evaluate on five languages and show that semi-supervised training provides a boost over unsupervised training, while the model selection method yields the best average results over all languages and is competitive with state-of-the-art semi-supervised systems. Moreover, this method provides the potential to tune performance according to different evaluation metrics or downstream tasks. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00225 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,235 |
article | satta-kuhlmann-2013-efficient | Efficient Parsing for Head-Split Dependency Trees | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1022/ | Satta, Giorgio and Kuhlmann, Marco | null | 267--278 | Head splitting techniques have been successfully exploited to improve the asymptotic runtime of parsing algorithms for projective dependency trees, under the arc-factored model. In this article we extend these techniques to a class of non-projective dependency trees, called well-nested dependency trees with block-degree at most 2, which has been previously investigated in the literature. We define a structural property that allows head splitting for these trees, and present two algorithms that improve over the runtime of existing algorithms at no significant loss in coverage. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00226 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,236 |
article | de-melo-bansal-2013-good | Good, Great, Excellent: Global Inference of Semantic Intensities | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1023/ | de Melo, Gerard and Bansal, Mohit | null | 279--290 | Adjectives like good, great, and excellent are similar in meaning, but differ in intensity. Intensity order information is very useful for language learners as well as in several NLP tasks, but is missing in most lexical resources (dictionaries, WordNet, and thesauri). In this paper, we present a primarily unsupervised approach that uses semantics from Web-scale data (e.g., phrases like good but not excellent) to rank words by assigning them positions on a continuous scale. We rely on Mixed Integer Linear Programming to jointly determine the ranks, such that individual decisions benefit from global information. When ranking English adjectives, our global algorithm achieves substantial improvements over previous work on both pairwise and rank correlation metrics (specifically, 70{\%} pairwise accuracy as compared to only 56{\%} by previous work). Moreover, our approach can incorporate external synonymy information (increasing its pairwise accuracy to 78{\%}) and extends easily to new languages. We also make our code and data freely available. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00227 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,237 |
article | wang-zong-2013-large | Large-scale Word Alignment Using Soft Dependency Cohesion Constraints | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1024/ | Wang, Zhiguo and Zong, Chengqing | null | 291--300 | Dependency cohesion refers to the observation that phrases dominated by disjoint dependency subtrees in the source language generally do not overlap in the target language. It has been verified to be a useful constraint for word alignment. However, previous work either treats this as a hard constraint or uses it as a feature in discriminative models, which is ineffective for large-scale tasks. In this paper, we take dependency cohesion as a soft constraint, and integrate it into a generative model for large-scale word alignment experiments. We also propose an approximate EM algorithm and a Gibbs sampling algorithm to estimate model parameters in an unsupervised manner. Experiments on large-scale Chinese-English translation tasks demonstrate that our model achieves improvements in both alignment quality and translation quality. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00228 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,238 |
article | sun-wan-2013-data | Data-driven, {PCFG}-based and Pseudo-{PCFG}-based Models for {C}hinese Dependency Parsing | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1025/ | Sun, Weiwei and Wan, Xiaojun | null | 301--314 | We present a comparative study of transition-, graph- and PCFG-based models aimed at illuminating more precisely the likely contribution of CFGs in improving Chinese dependency parsing accuracy, especially by combining heterogeneous models. Inspired by the impact of a constituency grammar on dependency parsing, we propose several strategies to acquire pseudo CFGs only from dependency annotations. Compared to linguistic grammars learned from rich phrase-structure treebanks, well designed pseudo grammars achieve similar parsing accuracy and have equivalent contributions to parser ensemble. Moreover, pseudo grammars increase the diversity of base models; therefore, together with all other models, further improve system combination. Based on automatic POS tagging, our final model achieves a UAS of 87.23{\%}, resulting in a significant improvement of the state of the art. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00229 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,239 |
article | luong-etal-2013-parsing | Parsing entire discourses as very long strings: Capturing topic continuity in grounded language learning | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1026/ | Luong, Minh-Thang and Frank, Michael C. and Johnson, Mark | null | 315--326 | Grounded language learning, the task of mapping from natural language to a representation of meaning, has attracted more and more interest in recent years. In most work on this topic, however, utterances in a conversation are treated independently and discourse structure information is largely ignored. In the context of language acquisition, this independence assumption discards cues that are important to the learner, e.g., the fact that consecutive utterances are likely to share the same referent (Frank et al., 2013). The current paper describes an approach to the problem of simultaneously modeling grounded language at the sentence and discourse levels. We combine ideas from parsing and grammar induction to produce a parser that can handle long input strings with thousands of tokens, creating parse trees that represent full discourses. By casting grounded language learning as a grammatical inference task, we use our parser to extend the work of Johnson et al. (2012), investigating the importance of discourse continuity in children`s language acquisition and its interaction with social cues. Our model boosts performance in a language acquisition task and yields good discourse segmentations compared with human annotators. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00230 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,240 |
article | bisazza-federico-2013-dynamically | Dynamically Shaping the Reordering Search Space of Phrase-Based Statistical Machine Translation | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1027/ | Bisazza, Arianna and Federico, Marcello | null | 327--340 | Defining the reordering search space is a crucial issue in phrase-based SMT between distant languages. In fact, the optimal trade-off between accuracy and complexity of decoding is nowadays reached by harshly limiting the input permutation space. We propose a method to dynamically shape such space and, thus, capture long-range word movements without hurting translation quality nor decoding time. The space defined by loose reordering constraints is dynamically pruned through a binary classifier that predicts whether a given input word should be translated right after another. The integration of this model into a phrase-based decoder improves a strong Arabic-English baseline already including state-of-the-art early distortion cost (Moore and Quirk, 2007) and hierarchical phrase orientation models (Galley and Manning, 2008). Significant improvements in the reordering of verbs are achieved by a system that is notably faster than the baseline, while bleu and meteor remain stable, or even increase, at a very high distortion limit. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00231 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,241 |
article | louis-nenkova-2013-makes | What Makes Writing Great? First Experiments on Article Quality Prediction in the Science Journalism Domain | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1028/ | Louis, Annie and Nenkova, Ani | null | 341--352 | Great writing is rare and highly admired. Readers seek out articles that are beautifully written, informative and entertaining. Yet information-access technologies lack capabilities for predicting article quality at this level. In this paper we present first experiments on article quality prediction in the science journalism domain. We introduce a corpus of great pieces of science journalism, along with typical articles from the genre. We implement features to capture aspects of great writing, including surprising, visual and emotional content, as well as general features related to discourse organization and sentence structure. We show that the distinction between great and typical articles can be detected fairly accurately, and that the entire spectrum of our features contribute to the distinction. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00232 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,242 |
article | turney-2013-distributional | Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1029/ | Turney, Peter D. | null | 353--366 | There have been several efforts to extend distributional semantics beyond individual words, to measure the similarity of word pairs, phrases, and sentences (briefly, tuples; ordered sets of words, contiguous or noncontiguous). One way to extend beyond words is to compare two tuples using a function that combines pairwise similarities between the component words in the tuples. A strength of this approach is that it works with both relational similarity (analogy) and compositional similarity (paraphrase). However, past work required hand-coding the combination function for different tasks. The main contribution of this paper is that combination functions are generated by supervised learning. We achieve state-of-the-art results in measuring relational similarity between word pairs (SAT analogies and SemEval 2012 Task 2) and measuring compositional similarity between noun-modifier phrases and unigrams (multiple-choice paraphrase questions). | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00233 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,243 |
article | ritter-etal-2013-modeling | Modeling Missing Data in Distant Supervision for Information Extraction | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1030/ | Ritter, Alan and Zettlemoyer, Luke and Mausam and Etzioni, Oren | null | 367--378 | Distant supervision algorithms learn information extraction models given only large readily available databases and text collections. Most previous work has used heuristics for generating labeled data, for example assuming that facts not contained in the database are not mentioned in the text, and facts in the database must be mentioned at least once. In this paper, we propose a new latent-variable approach that models missing data. This provides a natural way to incorporate side information, for instance modeling the intuition that text will often mention rare entities which are likely to be missing in the database. Despite the added complexity introduced by reasoning about missing data, we demonstrate that a carefully designed local search approach to inference is very accurate and scales to large datasets. Experiments demonstrate improved performance for binary and unary relation extraction when compared to learning with heuristic labels, including on average a 27{\%} increase in area under the precision recall curve in the binary case. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00234 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,244 |
article | li-etal-2013-data | Data-Driven Metaphor Recognition and Explanation | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1031/ | Li, Hongsong and Zhu, Kenny Q. and Wang, Haixun | null | 379--390 | Recognizing metaphors and identifying the source-target mappings is an important task as metaphorical text poses a big challenge for machine reading. To address this problem, we automatically acquire a metaphor knowledge base and an isA knowledge base from billions of web pages. Using the knowledge bases, we develop an inference mechanism to recognize and explain the metaphors in the text. To our knowledge, this is the first purely data-driven approach of probabilistic metaphor acquisition, recognition, and explanation. Our results shows that it significantly outperforms other state-of-the-art methods in recognizing and explaining metaphors. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00235 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,245 |
article | basu-etal-2013-powergrading | {P}owergrading: a Clustering Approach to Amplify Human Effort for Short Answer Grading | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1032/ | Basu, Sumit and Jacobs, Chuck and Vanderwende, Lucy | null | 391--402 | We introduce a new approach to the machine-assisted grading of short answer questions. We follow past work in automated grading by first training a similarity metric between student responses, but then go on to use this metric to group responses into clusters and subclusters. The resulting groupings allow teachers to grade multiple responses with a single action, provide rich feedback to groups of similar answers, and discover modalities of misunderstanding among students; we refer to this amplification of grader effort as {\textquotedblleft}powergrading.{\textquotedblright} We develop the means to further reduce teacher effort by automatically performing actions when an answer key is available. We show results in terms of grading progress with a small {\textquotedblleft}budget{\textquotedblright} of human actions, both from our method and an LDA-based approach, on a test corpus of 10 questions answered by 698 respondents. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00236 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,246 |
article | goldberg-nivre-2013-training | Training Deterministic Parsers with Non-Deterministic Oracles | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1033/ | Goldberg, Yoav and Nivre, Joakim | null | 403--414 | Greedy transition-based parsers are very fast but tend to suffer from error propagation. This problem is aggravated by the fact that they are normally trained using oracles that are deterministic and incomplete in the sense that they assume a unique canonical path through the transition system and are only valid as long as the parser does not stray from this path. In this paper, we give a general characterization of oracles that are nondeterministic and complete, present a method for deriving such oracles for transition systems that satisfy a property we call arc decomposition, and instantiate this method for three well-known transition systems from the literature. We say that these oracles are dynamic, because they allow us to dynamically explore alternative and nonoptimal paths during training {---} in contrast to oracles that statically assume a unique optimal path. Experimental evaluation on a wide range of data sets clearly shows that using dynamic oracles to train greedy parsers gives substantial improvements in accuracy. Moreover, this improvement comes at no cost in terms of efficiency, unlike other techniques like beam search. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00237 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,247 |
article | bohnet-etal-2013-joint | Joint Morphological and Syntactic Analysis for Richly Inflected Languages | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1034/ | Bohnet, Bernd and Nivre, Joakim and Boguslavsky, Igor and Farkas, Rich{\'a}rd and Ginter, Filip and Haji{\v{c}}, Jan | null | 415--428 | Joint morphological and syntactic analysis has been proposed as a way of improving parsing accuracy for richly inflected languages. Starting from a transition-based model for joint part-of-speech tagging and dependency parsing, we explore different ways of integrating morphological features into the model. We also investigate the use of rule-based morphological analyzers to provide hard or soft lexical constraints and the use of word clusters to tackle the sparsity of lexical features. Evaluation on five morphologically rich languages (Czech, Finnish, German, Hungarian, and Russian) shows consistent improvements in both morphological and syntactic accuracy for joint prediction over a pipeline model, with further improvements thanks to lexical constraints and word clusters. The final results improve the state of the art in dependency parsing for all languages. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00238 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,248 |
article | irvine-etal-2013-measuring | Measuring Machine Translation Errors in New Domains | Lin, Dekang and Collins, Michael | null | 2013 | Cambridge, MA | MIT Press | https://aclanthology.org/Q13-1035/ | Irvine, Ann and Morgan, John and Carpuat, Marine and Daum{\'e} III, Hal and Munteanu, Dragos | null | 429--440 | We develop two techniques for analyzing the effect of porting a machine translation system to a new domain. One is a macro-level analysis that measures how domain shift affects corpus-level evaluation; the second is a micro-level analysis for word-level errors. We apply these methods to understand what happens when a Parliament-trained phrase-based machine translation system is applied in four very different domains: news, medical texts, scientific articles and movie subtitles. We present quantitative and qualitative experiments that highlight opportunities for future research in domain adaptation for machine translation. | Transactions of the Association for Computational Linguistics | 1 | 10.1162/tacl_a_00239 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 70,249 |
inproceedings | cettolo-etal-2013-report | Report on the 10th {IWSLT} evaluation campaign | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.1/ | Cettolo, Mauro and Niehues, Jan and St{\"uker, Sebastian and Bentivogli, Luisa and Federico, Marcello | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | The paper overviews the tenth evaluation campaign organized by the IWSLT workshop. The 2013 evaluation offered multiple tracks on lecture transcription and translation based on the TED Talks corpus. In particular, this year IWSLT included two automatic speech recognition tracks, on English and German, three speech translation tracks, from English to French, English to German, and German to English, and three text translation track, also from English to French, English to German, and German to English. In addition to the official tracks, speech and text translation optional tracks were offered involving 12 other languages: Arabic, Spanish, Portuguese (B), Italian, Chinese, Polish, Persian, Slovenian, Turkish, Dutch, Romanian, Russian. Overall, 18 teams participated in the evaluation for a total of 217 primary runs submitted. All runs were evaluated with objective metrics on a current test set and two progress test sets, in order to compare the progresses against systems of the previous years. In addition, submissions of one of the official machine translation tracks were also evaluated with human post-editing. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,587 |
inproceedings | lo-wu-2013-human | Human semantic {MT} evaluation with {HMEANT} for {IWSLT} 2013 | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.2/ | Lo, Chi-kiu and Wu, Dekai | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | We present the results of large-scale human semantic MT evaluation with HMEANT on the IWSLT 2013 German-English MT and SLT tracks and show that HMEANT evaluates the performance of the MT systems differently compared to BLEU and TER. Together with the references, all the translations are annotated by annotators who are native English speakers in both semantic role labeling stage and role filler alignment stage of HMEANT. We obtain high inter-annotator agreement and low annotation time costs which indicate that it is feasible to run a large-scale human semantic MT evaluation campaign using HMEANT. Our results also show that HMEANT is a robust and reliable semantic MT evaluation metric for running large-scale evaluation campaigns as it is inexpensive and simple while maintaining the semantic representational transparency to provide a perspective which is different from BLEU and TER in order to understand the performance of the state-of-the-art MT systems. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,588 |
inproceedings | birch-etal-2013-english | {E}nglish {SLT} and {MT} system description for the {IWSLT} 2013 evaluation | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.3/ | Birch, Alexandra and Durrani, Nadir and Koehn, Philipp | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | This paper gives a description of the University of Edinburgh`s (UEDIN) systems for IWSLT 2013. We participated in all the MT tracks and the German-to-English and Englishto-French SLT tracks. Our SLT submissions experimented with including ASR uncertainty into the decoding process via confusion networks, and looked at different ways of punctuating ASR output. Our MT submissions are mainly based on a system used in the recent evaluation campaign at the Workshop on Statistical Machine Translation [1]. We additionally explored the use of generalized representations (Brown clusters, POS and morphological tags) translating out of English into European languages. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,589 |
inproceedings | aue-etal-2013-msr | {MSR}-{FBK} {IWSLT} 2013 {SLT} system description | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.4/ | Aue, Anthony and Gao, Qin and Hassan, Hany and He, Xiaodong and Li, Gang and Ruiz, Nicholas and Seide, Frank | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | This paper describes the systems used for the MSR+FBK submission for the SLT track of IWSLT 2013. Starting from a baseline system we made a series of iterative and additive improvements, including a novel method for processing bilingual data used to train MT systems for use on ASR output. Our primary submission is a system combination of five individual systems, combining the output of multiple ASR engines with multiple MT techniques. There are two contrastive submissions to help place the combined system in context. We describe the systems used and present results on the test sets. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,590 |
inproceedings | lo-etal-2013-improving-machine | Improving machine translation into {C}hinese by tuning against {C}hinese {MEANT} | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.5/ | Lo, Chi-kiu and Beloucif, Meriem and Wu, Dekai | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | We present the first ever results showing that Chinese MT output is significantly improved by tuning a MT system against a semantic frame based objective function, MEANT, rather than an n-gram based objective function, BLEU, as measured across commonly used metrics and different test sets. Recent work showed that by preserving the meaning of the translations as captured by semantic frames in the training process, MT systems for translating into English on both formal and informal genres are constrained to produce more adequate translations by making more accurate choices on lexical output and reordering rules. In this paper we describe our experiments in IWSLT 2013 TED talk MT tasks on tuning MT systems against MEANT for translating into Chinese and English respectively. We show that the Chinese translation output benefits more from tuning a MT system against MEANT than the English translation output due to the ambiguous nature of word boundaries in Chinese. Our encouraging results show that using MEANT is a promising alternative to BLEU in both evaluating and tuning MT systems to drive the progress of MT research across different languages. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,591 |
inproceedings | huang-etal-2013-nict | The {NICT} {ASR} system for {IWSLT} 2013 | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.6/ | Huang, Chien-Lin and Dixon, Paul R. and Matsuda, Shigeki and Wu, Youzheng and Lu, Xugang and Saiko, Masahiro and Hori, Chiori | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | This study presents the NICT automatic speech recognition (ASR) system submitted for the IWSLT 2013 ASR evaluation. We apply two types of acoustic features and three types of acoustic models to the NICT ASR system. Our system is comprised of six subsystems with different acoustic features and models. This study reports the individual results and fusion of systems and highlights the improvements made by our proposed methods that include the automatic segmentation of audio data, language model adaptation, speaker adaptive training of deep neural network models, and the NICT SprinTra decoder. Our experimental results indicated that our proposed methods offer good performance improvements on lecture speech recognition tasks. Our results denoted a 13.5{\%} word error rate on the IWSLT 2013 ASR English test data set. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,592 |
inproceedings | falavigna-etal-2013-fbk | {FBK} @ {IWSLT} 2013 {--} {ASR} tracks | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.7/ | Falavigna, Daniele and Gretter, Roberto and Brugnara, Fabio and Giuliani, Diego | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | This paper reports on the participation of FBK at the IWSLT2013 evaluation campaign on automatic speech recognition (ASR): precisely on both English and German ASR track. Only primary submissions have been sent for evaluation. For English, the ASR system features acoustic models trained on a portion of the TED talk recordings that was automatically selected according to the fidelity of the provided transcriptions. Two decoding steps are performed interleaved by acoustic feature normalization and acoustic model adaptation. A final step combines the outputs obtained after having rescored the word graphs generated in the second decoding step with 4 different language models. The latter are trained on: out-of-domain text data, in-domain data and several sets of automatically selected data. For German, acoustic models have been trained on automatically selected portions of a broadcast news corpus, called {\textquotedblright}Euronews{\textquotedblright}. Differently from English, in this case only two decoding steps are carried out without making use of any rescoring procedure. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,593 |
inproceedings | sajjad-etal-2013-qcri-iwslt | {QCRI} at {IWSLT} 2013: experiments in {A}rabic-{E}nglish and {E}nglish-{A}rabic spoken language translation | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.8/ | Sajjad, Hassan and Guzm{\'a}n, Francisco and Nakov, Preslav and Abdelali, Ahmed and Murray, Kenton and Al Obaidli, Fahad and Vogel, Stephan | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | We describe the Arabic-English and English-Arabic statistical machine translation systems developed by the Qatar Computing Research Institute for the IWSLT`2013 evaluation campaign on spoken language translation. We used one phrase-based and two hierarchical decoders, exploring various settings thereof. We further experimented with three domain adaptation methods, and with various Arabic word segmentation schemes. Combining the output of several systems yielded a gain of up to 3.4 BLEU points over the baseline. Here we also describe a specialized normalization scheme for evaluating Arabic output, which was adopted for the IWSLT`2013 evaluation campaign. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,594 |
inproceedings | na-lee-2013-discriminative | A discriminative reordering parser for {IWSLT} 2013 | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.9/ | Na, Hwidong and Lee, Jong-Hyeok | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | We participated in the IWSLT 2013 Evaluation Campaign for the MT track for two official directions: German{\ensuremath{\leftrightarrow}}English. Our system consisted of a reordering module and a statistical machine translation (SMT) module under a pre-ordering SMT framework. We trained the reordering module using three scalable methods in order to utilize training instances as many as possible. The translation quality of our primary submissions were comparable to that of a hierarchical phrasebased SMT, which usually requires a longer time to decode. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,595 |
inproceedings | wuebker-etal-2013-rwth | The {RWTH} {A}achen machine translation systems for {IWSLT} 2013 | Zhang, Joy Ying | dec # " 5-6" | 2013 | Heidelberg, Germany | null | https://aclanthology.org/2013.iwslt-evaluation.10/ | Wuebker, Joern and Peitz, Stephan and Alkhouli, Tamer and Peter, Jan-Thorsten and Feng, Minwei and Freitag, Markus and Ney, Hermann | Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign | null | This work describes the statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign International Workshop on Spoken Language Translation (IWSLT) 2013. We participated in the English{\textrightarrow}French, English{\ensuremath{\leftrightarrow}}German, Arabic{\textrightarrow}English, Chinese{\textrightarrow}English and Slovenian{\ensuremath{\leftrightarrow}}English MT tracks and the English{\textrightarrow}French and English{\textrightarrow}German SLT tracks. We apply phrase-based and hierarchical SMT decoders, which are augmented by state-of-the-art extensions. The novel techniques we experimentally evaluate include discriminative phrase training, a continuous space language model, a hierarchical reordering model, a word class language model, domain adaptation via data selection and system combination of standard and reverse order models. By application of these methods we can show considerable improvements over the respective baseline systems. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | 71,596 |
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