A Bayesian Approach to Phoneme Detection for Uyghur

In this paper, we presented a semantic speech segmentation approach, in particular phoneme segmentation. In order to get phoneme level information, a novel voiced speech, unvoiced speech and silence (VUS) classification is proposed. Five parameters that can be extracted by short-time analysis methods are used to discriminate the phoneme boundary. Experiments on Uyghur broadcasting news indicate that the performance of proposed algorithm is satisfying.