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README.md

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-license: cc-by-nc-4.0
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+## 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
+---