In order to improve the flexibility and the precision of an automatic phone segmentation system for a type of expressive speech, the dubbing into French of fiction movies, we developed both the phonetic labeling process and the alignment process. The automatic labelling system relies on an automatic grapheme-to-phoneme conversion including all the variants of the phonetic chain and on HMM modeling. In this article, we will distinguish three sets of phone models: a set of context independent models, a set of left and right context dependant models and finally a mixing of the two that combines phone and triphone models according to the precision of alignment obtained for each phonetic broad-class. The three models are evaluated on a test corpus. On the one hand we notice a little decrease in the score of phonetic labelling mainly due to pauses insertions, but on the other hand the mixed set of models gives the best results for the score of precision of the alignment.