Create README.md

README.md

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+---
+language:
+- ar
+pretty_name: TunSwitch
+---
+
+This folder contains the data used to develop and test the Tunisian Arabic Automatic Speech Recognition model developed in the following paper :
+
+A. A. Ben Abdallah*, A. Kabboudi, A. Kanoun, and S. Zaiem*, “Leveraging data collection and unsupervised learning for code-switched tunisian arabic automatic speech recognition”, Submitted to ICASSP 2024, vol. * : These two authors have contributed equally. 2023.
+
+
+It contains 4 zipped folders containing audio data :
+- TunSwitchCS.zip : containing annotated code-switched data.
+- TunSwitchTO.zip : containing annotated Tunisian-Only data.
+- weakly_labeled_tn.zip : containing weakly-labeled (or unlabeled) audio data. Audios may contain code-switching, but the current weak labels do not.
+- test_wavs.zip : contains annotated testing data, divided between a code-switched part and a tunisian-only part.
+
+
+It also contains textual data, used for language modelling, contained in TextData.zip. Finally it also contains a language-detailed annotation of TunSwitchCS in the  language_annotation.zip file .
+
+More details about the data are available in the paper. The current table are in a SpeechBrain-friendly format, the column path is irrelevant and has to be changed according to your local setting. Please use the provided train-dev-test splits if you work with this dataset.
+
+Please cite the aforementioned paper if you use or refer to this dataset. You can find models trained and tested on this dataset Here. Space demos are also available. 
+
+If you use or refer to this dataset, please cite : 
+
+```
+
+@misc{abdallah2023leveraging,
+      title={Leveraging Data Collection and Unsupervised Learning for Code-switched Tunisian Arabic Automatic Speech Recognition}, 
+      author={Ahmed Amine Ben Abdallah and Ata Kabboudi and Amir Kanoun and Salah Zaiem},
+      year={2023},
+      eprint={2309.11327},
+      archivePrefix={arXiv},
+      primaryClass={eess.AS}
+}
+
+```