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Arabic Phonetic Dictionaries for Speech Recognition

Arabic Phonetic Dictionaries for Speech Recognition

Mohamed Ali, Moustafa Elshafei, Mansour Al-Ghamdi, Husni Al-Muhtaseb
Copyright: © 2009 |Volume: 2 |Issue: 4 |Pages: 14
ISSN: 1938-7857|EISSN: 1938-7865|ISSN: 1938-7857|EISBN13: 9781616920722|EISSN: 1938-7865|DOI: 10.4018/jitr.2009062905
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MLA

Ali, Mohamed, et al. "Arabic Phonetic Dictionaries for Speech Recognition." JITR vol.2, no.4 2009: pp.67-80. http://doi.org/10.4018/jitr.2009062905

APA

Ali, M., Elshafei, M., Al-Ghamdi, M., & Al-Muhtaseb, H. (2009). Arabic Phonetic Dictionaries for Speech Recognition. Journal of Information Technology Research (JITR), 2(4), 67-80. http://doi.org/10.4018/jitr.2009062905

Chicago

Ali, Mohamed, et al. "Arabic Phonetic Dictionaries for Speech Recognition," Journal of Information Technology Research (JITR) 2, no.4: 67-80. http://doi.org/10.4018/jitr.2009062905

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Abstract

Phonetic dictionaries are essential components of large-vocabulary speaker-independent speech recognition systems. This paper presents a rule-based technique to generate phonetic dictionaries for a large vocabulary Arabic speech recognition system. The system used conventional Arabic pronunciation rules, common pronunciation rules of Modern Standard Arabic, as well as some common dialectal cases. The paper gives in detail an explanation of these rules as well as their formal mathematical presentation. The rules were used to generate a dictionary for a 5.4 hour corpus of broadcast news. The rules and the phone set were tested and evaluated on an Arabic speech recognition system. The system was trained on 4.3 hours of the 5.4 hours of Arabic broadcast news corpus and tested on the remaining 1.1 hours. The phonetic dictionary contains 23,841 definitions corresponding to about 14232 words. The language model contains both bi-grams and tri-grams. The Word Error Rate (WER) came to 9.0%.

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