Grapheme to phoneme conversion: an Arabic dialect case
نویسندگان
چکیده
We aim to develop a Speech-to-Speech translation system between Modern Standard Arabic and Algiers dialect. Such a system must include a Text-to-Speech module which itself must include a Grapheme-to-Phoneme converter. Algiers dialect is an Arabic dialect concerned by the most problems of Modern Standard Arabic in NLP area. Furthermore, it could be considered as an under-resourced language because it is a vernacular language for which no substantial corpus exists. In this paper we present a grapheme-to-phoneme converter for this language. We used a rule based approach and a statistical approach, we got an accuracy of 92% VS 85% despite the lack of resource for this language. Index Terms Modern Standard Arabic (MSA), Algiers Dialect, Grapheme-to-phoneme conversion, Statistical Machine Translation.
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