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## TARIC-SLU: A Tunisian Benchmark Dataset For Spoken Language Understanding |
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The primary contributions of this work are as follows: |
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1. Release of the TARIC-SLU corpus: The very first resource of its kind designed for SLU within the Tunisian dialect |
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2. Comprehensive exposition of the semantic representations and annotation methodologies employed in the construction of the TARIC-SLU corpus. |
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3. Release of an open-source SpeechBrain recipe to build the semantic tasks inherent to the TARIC-SLU dataset. |
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4. Provides baseline results for Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Spoken Language Understanding (SLU) tasks, all derived from the TARIC-SLU corpus. |
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If you use TARIC-SLU in your research, please cite it using the following BibTeX entry: |
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```bibtex |
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@inproceedings{mdhaffar-etal-2024-taric-slu, |
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title = "{TARIC}-{SLU}: A {T}unisian Benchmark Dataset for Spoken Language Understanding", |
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author = "Mdhaffar, Salima and Bougares, Fethi and de Mori, Renato and Zaiem, Salah and Ravanelli, Mirco and Est{\`e}ve, Yannick", |
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editor = "Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen", |
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booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)", |
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month = may, |
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year = "2024", |
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address = "Torino, Italia", |
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publisher = "ELRA and ICCL", |
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url = "https://aclanthology.org/2024.lrec-main.1357", |
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pages = "15606--15616" |
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``` |
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#TARIC-SLU |
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Download link : https://demo-lia.univ-avignon.fr/taric-dataset/ |
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--- |
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license: cc-by-nc-4.0 |
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--- |
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