Hierarchical phoneme discrimination by hidden Markov modelling using cepstrum and formant information
作者： Y. Ariki , F.R. McInnes , M.A. Jack
DOI: 10.1109/ICASSP.1989.266514
关键词:
摘要: A report is presented of comparative results for vowel classification using hidden Markov models based on linear predictive coding (LPC)-based cepstral vectors and formant features. The accuracy shown to be significantly improved by time duration constraints in feature space, especially the mel-frequency representation its derivative. highest recognition obtained integrating two spaces, multiplying probabilities computed separate spaces. This improvement extended more general phoneme task use a hierarchical integration method, which utilizes space together with consonant LPC-based space. >
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