qcri/Arabic_speech_code_switching
The first Dialectal Arabic Code Switching - DACS corpus from broadcast speech. Annotated at the token-level, considering both the linguistic and the acoustic cues. This dataset is a potential benchmark for DCS in spontaneous speech.
This dataset provides two hours of Egyptian Arabic broadcast speech, carefully segmented and transcribed, with each word annotated to identify instances of code-switching. It takes raw audio and ASR transcriptions, producing a detailed record of word-level language mixture (Modern Standard Arabic, Egyptian dialect, mixed, or foreign words) within spoken sentences. Researchers and developers working on Arabic speech technologies will find this valuable for training and evaluating models.
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Use this if you are developing or evaluating speech recognition, natural language processing, or language identification systems specifically for dialectal Arabic that frequently involves code-switching.
Not ideal if you are looking for a general-purpose Arabic speech corpus without a focus on code-switching or if your primary interest is written text analysis.
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Apr 03, 2022
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