Automatic Speech Recognition for Tunisian Dialect
نویسندگان
چکیده
Speech recognition for under-resourced languages represents an active field of research during the past decade. The tunisian arabic dialect has been chosen as a typical example for an under-resourced Arabic dialect. We propose, in this paper, our first steps to build an automatic speech recognition system for Tunisian dialect. Several Acoustic Models have been trained using HMM-GMM and HMM-DNN system. The speech corpus has been collected and transcribed from dialogues in the Tunisian Railway Transport Network. The HMM-DNN system can give an impressive relative reduction in WER.
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