Phoneme classification using semicontinuous hidden Markov models
作者： X.D. Huang
DOI: 10.1109/78.134469
关键词:
摘要: Speaker-dependent phoneme recognition experiments were conducted using variants of the semicontinuous hidden Markov model (SCHMM) with explicit state duration modeling. Results clearly demonstrated that SCHMM offers significantly improved classification accuracy compared to both discrete HMM and continuous HMM; error rate was reduced by more than 30% 20%, respectively. The use a limited number mixture densities amount computation. Explicit modeling further rate. >
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