While Modern Standard Arabic is the formal spoken and written language of the Arab world, dialects are the major com-munication mode for everyday life; identifying a speaker's di-alect is thus critical to speech processing tasks such as automatic speech recognition, as well as speaker identification. We exam-ine the role of prosodic features (intonation and rhythm) across four Arabic dialects: Gulf, Iraqi, Levantine, and Egyptian, for the purpose of automatic dialect identification. We show that prosodic features can significantly improve identification, over a purely phonotactic-based approach, with an identification ac-curacy of 86.33% for 2m utterances.
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