Datasets:
Size:
10K<n<100K
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - expert-generated | |
| language: | |
| - de | |
| - en | |
| - es | |
| - fr | |
| - it | |
| license: | |
| - cc-by-sa-4.0 | |
| multilinguality: | |
| - multilingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-generation | |
| - fill-mask | |
| - text-classification | |
| task_ids: | |
| - dialogue-modeling | |
| - language-modeling | |
| - masked-language-modeling | |
| pretty_name: MIAM | |
| tags: | |
| - dialogue-act-classification | |
| dataset_info: | |
| - config_name: dihana | |
| features: | |
| - name: Speaker | |
| dtype: string | |
| - name: Utterance | |
| dtype: string | |
| - name: Dialogue_Act | |
| dtype: string | |
| - name: Dialogue_ID | |
| dtype: string | |
| - name: File_ID | |
| dtype: string | |
| - name: Label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Afirmacion | |
| '1': Apertura | |
| '2': Cierre | |
| '3': Confirmacion | |
| '4': Espera | |
| '5': Indefinida | |
| '6': Negacion | |
| '7': No_entendido | |
| '8': Nueva_consulta | |
| '9': Pregunta | |
| '10': Respuesta | |
| - name: Idx | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 1946735 | |
| num_examples: 19063 | |
| - name: validation | |
| num_bytes: 216498 | |
| num_examples: 2123 | |
| - name: test | |
| num_bytes: 238446 | |
| num_examples: 2361 | |
| download_size: 1777267 | |
| dataset_size: 2401679 | |
| - config_name: ilisten | |
| features: | |
| - name: Speaker | |
| dtype: string | |
| - name: Utterance | |
| dtype: string | |
| - name: Dialogue_Act | |
| dtype: string | |
| - name: Dialogue_ID | |
| dtype: string | |
| - name: Label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': AGREE | |
| '1': ANSWER | |
| '2': CLOSING | |
| '3': ENCOURAGE-SORRY | |
| '4': GENERIC-ANSWER | |
| '5': INFO-REQUEST | |
| '6': KIND-ATTITUDE_SMALL-TALK | |
| '7': OFFER-GIVE-INFO | |
| '8': OPENING | |
| '9': PERSUASION-SUGGEST | |
| '10': QUESTION | |
| '11': REJECT | |
| '12': SOLICITATION-REQ_CLARIFICATION | |
| '13': STATEMENT | |
| '14': TALK-ABOUT-SELF | |
| - name: Idx | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 244336 | |
| num_examples: 1986 | |
| - name: validation | |
| num_bytes: 33988 | |
| num_examples: 230 | |
| - name: test | |
| num_bytes: 145376 | |
| num_examples: 971 | |
| download_size: 349993 | |
| dataset_size: 423700 | |
| - config_name: loria | |
| features: | |
| - name: Speaker | |
| dtype: string | |
| - name: Utterance | |
| dtype: string | |
| - name: Dialogue_Act | |
| dtype: string | |
| - name: Dialogue_ID | |
| dtype: string | |
| - name: File_ID | |
| dtype: string | |
| - name: Label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': ack | |
| '1': ask | |
| '2': find_mold | |
| '3': find_plans | |
| '4': first_step | |
| '5': greet | |
| '6': help | |
| '7': inform | |
| '8': inform_engine | |
| '9': inform_job | |
| '10': inform_material_space | |
| '11': informer_conditioner | |
| '12': informer_decoration | |
| '13': informer_elcomps | |
| '14': informer_end_manufacturing | |
| '15': kindAtt | |
| '16': manufacturing_reqs | |
| '17': next_step | |
| '18': 'no' | |
| '19': other | |
| '20': quality_control | |
| '21': quit | |
| '22': reqRep | |
| '23': security_policies | |
| '24': staff_enterprise | |
| '25': staff_job | |
| '26': studies_enterprise | |
| '27': studies_job | |
| '28': todo_failure | |
| '29': todo_irreparable | |
| '30': 'yes' | |
| - name: Idx | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 1208730 | |
| num_examples: 8465 | |
| - name: validation | |
| num_bytes: 133829 | |
| num_examples: 942 | |
| - name: test | |
| num_bytes: 149855 | |
| num_examples: 1047 | |
| download_size: 1221132 | |
| dataset_size: 1492414 | |
| - config_name: maptask | |
| features: | |
| - name: Speaker | |
| dtype: string | |
| - name: Utterance | |
| dtype: string | |
| - name: Dialogue_Act | |
| dtype: string | |
| - name: Dialogue_ID | |
| dtype: string | |
| - name: File_ID | |
| dtype: string | |
| - name: Label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': acknowledge | |
| '1': align | |
| '2': check | |
| '3': clarify | |
| '4': explain | |
| '5': instruct | |
| '6': query_w | |
| '7': query_yn | |
| '8': ready | |
| '9': reply_n | |
| '10': reply_w | |
| '11': reply_y | |
| - name: Idx | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 1910120 | |
| num_examples: 25382 | |
| - name: validation | |
| num_bytes: 389879 | |
| num_examples: 5221 | |
| - name: test | |
| num_bytes: 396947 | |
| num_examples: 5335 | |
| download_size: 1729021 | |
| dataset_size: 2696946 | |
| - config_name: vm2 | |
| features: | |
| - name: Utterance | |
| dtype: string | |
| - name: Dialogue_Act | |
| dtype: string | |
| - name: Speaker | |
| dtype: string | |
| - name: Dialogue_ID | |
| dtype: string | |
| - name: Label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': ACCEPT | |
| '1': BACKCHANNEL | |
| '2': BYE | |
| '3': CLARIFY | |
| '4': CLOSE | |
| '5': COMMIT | |
| '6': CONFIRM | |
| '7': DEFER | |
| '8': DELIBERATE | |
| '9': DEVIATE_SCENARIO | |
| '10': EXCLUDE | |
| '11': EXPLAINED_REJECT | |
| '12': FEEDBACK | |
| '13': FEEDBACK_NEGATIVE | |
| '14': FEEDBACK_POSITIVE | |
| '15': GIVE_REASON | |
| '16': GREET | |
| '17': INFORM | |
| '18': INIT | |
| '19': INTRODUCE | |
| '20': NOT_CLASSIFIABLE | |
| '21': OFFER | |
| '22': POLITENESS_FORMULA | |
| '23': REJECT | |
| '24': REQUEST | |
| '25': REQUEST_CLARIFY | |
| '26': REQUEST_COMMENT | |
| '27': REQUEST_COMMIT | |
| '28': REQUEST_SUGGEST | |
| '29': SUGGEST | |
| '30': THANK | |
| - name: Idx | |
| dtype: int32 | |
| splits: | |
| - name: train | |
| num_bytes: 1869254 | |
| num_examples: 25060 | |
| - name: validation | |
| num_bytes: 209390 | |
| num_examples: 2860 | |
| - name: test | |
| num_bytes: 209032 | |
| num_examples: 2855 | |
| download_size: 1641453 | |
| dataset_size: 2287676 | |
| config_names: | |
| - dihana | |
| - ilisten | |
| - loria | |
| - maptask | |
| - vm2 | |
| # Dataset Card for MIAM | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [N/A] | |
| - **Repository:** [N/A] | |
| - **Paper:** [N/A] | |
| - **Leaderboard:** [N/A] | |
| - **Point of Contact:** [N/A] | |
| ### Dataset Summary | |
| Multilingual dIalogAct benchMark is a collection of resources for training, evaluating, and | |
| analyzing natural language understanding systems specifically designed for spoken language. Datasets | |
| are in English, French, German, Italian and Spanish. They cover a variety of domains including | |
| spontaneous speech, scripted scenarios, and joint task completion. All datasets contain dialogue act | |
| labels. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| English, French, German, Italian, Spanish. | |
| ## Dataset Structure | |
| ### Data Instances | |
| #### Dihana Corpus | |
| For the `dihana` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'U', | |
| 'Utterance': 'Hola , quería obtener el horario para ir a Valencia', | |
| 'Dialogue_Act': 9, # 'Pregunta' ('Request') | |
| 'Dialogue_ID': '0', | |
| 'File_ID': 'B209_BA5c3', | |
| } | |
| ``` | |
| #### iLISTEN Corpus | |
| For the `ilisten` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'T_11_U11', | |
| 'Utterance': 'ok, grazie per le informazioni', | |
| 'Dialogue_Act': 6, # 'KIND-ATTITUDE_SMALL-TALK' | |
| 'Dialogue_ID': '0', | |
| } | |
| ``` | |
| #### LORIA Corpus | |
| For the `loria` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'Samir', | |
| 'Utterance': 'Merci de votre visite, bonne chance, et à la prochaine !', | |
| 'Dialogue_Act': 21, # 'quit' | |
| 'Dialogue_ID': '5', | |
| 'File_ID': 'Dial_20111128_113927', | |
| } | |
| ``` | |
| #### HCRC MapTask Corpus | |
| For the `maptask` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Speaker': 'f', | |
| 'Utterance': 'is it underneath the rope bridge or to the left', | |
| 'Dialogue_Act': 6, # 'query_w' | |
| 'Dialogue_ID': '0', | |
| 'File_ID': 'q4ec1', | |
| } | |
| ``` | |
| #### VERBMOBIL | |
| For the `vm2` configuration one example from the dataset is: | |
| ``` | |
| { | |
| 'Utterance': 'ja was sind viereinhalb Stunden Bahngerüttel gegen siebzig Minuten Turbulenzen im Flugzeug', | |
| 'Utterance': 'Utterance', | |
| 'Dialogue_Act': 'Dialogue_Act', # 'INFORM' | |
| 'Speaker': 'A', | |
| 'Dialogue_ID': '66', | |
| } | |
| ``` | |
| ### Data Fields | |
| For the `dihana` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'Afirmacion' (0) [Feedback_positive], 'Apertura' (1) [Opening], 'Cierre' (2) [Closing], 'Confirmacion' (3) [Acknowledge], 'Espera' (4) [Hold], 'Indefinida' (5) [Undefined], 'Negacion' (6) [Feedback_negative], 'No_entendido' (7) [Request_clarify], 'Nueva_consulta' (8) [New_request], 'Pregunta' (9) [Request] or 'Respuesta' (10) [Reply]. | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `ilisten` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'AGREE' (0), 'ANSWER' (1), 'CLOSING' (2), 'ENCOURAGE-SORRY' (3), 'GENERIC-ANSWER' (4), 'INFO-REQUEST' (5), 'KIND-ATTITUDE_SMALL-TALK' (6), 'OFFER-GIVE-INFO' (7), 'OPENING' (8), 'PERSUASION-SUGGEST' (9), 'QUESTION' (10), 'REJECT' (11), 'SOLICITATION-REQ_CLARIFICATION' (12), 'STATEMENT' (13) or 'TALK-ABOUT-SELF' (14). | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| For the `loria` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'ack' (0), 'ask' (1), 'find_mold' (2), 'find_plans' (3), 'first_step' (4), 'greet' (5), 'help' (6), 'inform' (7), 'inform_engine' (8), 'inform_job' (9), 'inform_material_space' (10), 'informer_conditioner' (11), 'informer_decoration' (12), 'informer_elcomps' (13), 'informer_end_manufacturing' (14), 'kindAtt' (15), 'manufacturing_reqs' (16), 'next_step' (17), 'no' (18), 'other' (19), 'quality_control' (20), 'quit' (21), 'reqRep' (22), 'security_policies' (23), 'staff_enterprise' (24), 'staff_job' (25), 'studies_enterprise' (26), 'studies_job' (27), 'todo_failure' (28), 'todo_irreparable' (29), 'yes' (30) | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `maptask` configuration, the different fields are: | |
| - `Speaker`: identifier of the speaker as a string. | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialog act label of the utterance. It can be one of 'acknowledge' (0), 'align' (1), 'check' (2), 'clarify' (3), 'explain' (4), 'instruct' (5), 'query_w' (6), 'query_yn' (7), 'ready' (8), 'reply_n' (9), 'reply_w' (10) or 'reply_y' (11). | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| - `File_ID`: identifier of the source file as a string. | |
| For the `vm2` configuration, the different fields are: | |
| - `Utterance`: Utterance as a string. | |
| - `Dialogue_Act`: Dialogue act label of the utterance. It can be one of 'ACCEPT' (0), 'BACKCHANNEL' (1), 'BYE' (2), 'CLARIFY' (3), 'CLOSE' (4), 'COMMIT' (5), 'CONFIRM' (6), 'DEFER' (7), 'DELIBERATE' (8), 'DEVIATE_SCENARIO' (9), 'EXCLUDE' (10), 'EXPLAINED_REJECT' (11), 'FEEDBACK' (12), 'FEEDBACK_NEGATIVE' (13), 'FEEDBACK_POSITIVE' (14), 'GIVE_REASON' (15), 'GREET' (16), 'INFORM' (17), 'INIT' (18), 'INTRODUCE' (19), 'NOT_CLASSIFIABLE' (20), 'OFFER' (21), 'POLITENESS_FORMULA' (22), 'REJECT' (23), 'REQUEST' (24), 'REQUEST_CLARIFY' (25), 'REQUEST_COMMENT' (26), 'REQUEST_COMMIT' (27), 'REQUEST_SUGGEST' (28), 'SUGGEST' (29), 'THANK' (30). | |
| - `Speaker`: Speaker as a string. | |
| - `Dialogue_ID`: identifier of the dialogue as a string. | |
| ### Data Splits | |
| | Dataset name | Train | Valid | Test | | |
| | ------------ | ----- | ----- | ---- | | |
| | dihana | 19063 | 2123 | 2361 | | |
| | ilisten | 1986 | 230 | 971 | | |
| | loria | 8465 | 942 | 1047 | | |
| | maptask | 25382 | 5221 | 5335 | | |
| | vm2 | 25060 | 2860 | 2855 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| Anonymous. | |
| ### Licensing Information | |
| This work is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Unported License](https://creativecommons.org/licenses/by-sa/4.0/). | |
| ### Citation Information | |
| ``` | |
| @inproceedings{colombo-etal-2021-code, | |
| title = "Code-switched inspired losses for spoken dialog representations", | |
| author = "Colombo, Pierre and | |
| Chapuis, Emile and | |
| Labeau, Matthieu and | |
| Clavel, Chlo{\'e}", | |
| booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing", | |
| month = nov, | |
| year = "2021", | |
| address = "Online and Punta Cana, Dominican Republic", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2021.emnlp-main.656", | |
| doi = "10.18653/v1/2021.emnlp-main.656", | |
| pages = "8320--8337", | |
| abstract = "Spoken dialogue systems need to be able to handle both multiple languages and multilinguality inside a conversation (\textit{e.g} in case of code-switching). In this work, we introduce new pretraining losses tailored to learn generic multilingual spoken dialogue representations. The goal of these losses is to expose the model to code-switched language. In order to scale up training, we automatically build a pretraining corpus composed of multilingual conversations in five different languages (French, Italian, English, German and Spanish) from OpenSubtitles, a huge multilingual corpus composed of 24.3G tokens. We test the generic representations on MIAM, a new benchmark composed of five dialogue act corpora on the same aforementioned languages as well as on two novel multilingual tasks (\textit{i.e} multilingual mask utterance retrieval and multilingual inconsistency identification). Our experiments show that our new losses achieve a better performance in both monolingual and multilingual settings.", | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@eusip](https://github.com/eusip) and [@PierreColombo](https://github.com/PierreColombo) for adding this dataset. |