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Erschienen in: International Journal of Speech Technology 4/2012

01.12.2012

Speaker-independent ASR for Modern Standard Arabic: effect of regional accents

verfasst von: Ghania Droua-Hamdani, Sid-Ahmed Selouani, Malika Boudraa

Erschienen in: International Journal of Speech Technology | Ausgabe 4/2012

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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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Literatur
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Metadaten
Titel
Speaker-independent ASR for Modern Standard Arabic: effect of regional accents
verfasst von
Ghania Droua-Hamdani
Sid-Ahmed Selouani
Malika Boudraa
Publikationsdatum
01.12.2012
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 4/2012
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-012-9146-4

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