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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 folder language_annotation/ . 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. |