This paper presents an automatic grapheme to phoneme conversion system that uses statistical machine translation techniques provided by the Moses Toolkit. The generated word pronunciations are employed in the dictionary of an automatic speech recognition system and evaluated using the ESTER 2 French broadcast news corpus. Grapheme to phoneme conversion based on Moses is compared to two other methods: G2P, and a dictionary look-up method supplemented by a rule-based tool for phonetic transcriptions of words unavailable in the dictionary. Moses gives better results than G2P, and have performance comparable to the dictionary look-up strategy.