This paper describes the refinement of the automatic speech segmentation into phones obtained via Hidden Markov Models (HMM). This refinement is based on acoustic-phonetic features associated to different phone classes. The proposed system was evaluated using both a small speaker dependent Brazilian Portuguese speech database and a speaker independent speech database (TIMIT). The refinement was applied to the boundaries obtained by just running the Viterbi's algorithm on the HMMs associated to the different utterances. Improvements of 30% and 13% were achieved in the percentage of segmentation errors below 20 ms for the speaker dependent and speaker independent databases respectively.
Bibliographic reference. Selmini, Antonio Marcos / Violaro, Fábio (2007): "Acoustic-phonetic features for refining the explicit speech segmentation", In INTERSPEECH-2007, 1314-1317.