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Type: Artigo de evento
Title: Acoustic-phonetic Features For Refining The Explicit Speech Segmentation
Author: Selmini A.M.
Violaro F.
Abstract: 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.
Rights: fechado
Identifier DOI: 
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

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