Abstract
This paper deals with speaker-independent Automatic Speech Recognition (ASR) system for continuous speech. This ASR system has been developed for Modern Standard Arabic (MSA) using recordings of six regions taken from ALGerian Arabic Speech Database (ALGASD), and has been designed by using Hidden Markov Models.
The main purpose of this study is to investigate the effect of regional accent on speech recognition rates. First, the experiment assessed the general performance of the model for the data speech of six regions, details of the recognition results are performed to observe the deterioration of the performance of the ASR according to the regional variation included in the speech material. The results have shown that the ASR performance is clearly impacted by the regional accents of the speakers.
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Droua-Hamdani, G., Selouani, SA. & Boudraa, M. Speaker-independent ASR for Modern Standard Arabic: effect of regional accents. Int J Speech Technol 15, 487–493 (2012). https://doi.org/10.1007/s10772-012-9146-4
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DOI: https://doi.org/10.1007/s10772-012-9146-4