We aim to develop a 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-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.