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