论文信息 - Phonetic recognition in a segment-based HMM

Phonetic recognition in a segment-based HMM

The author describes a segment-based HMM (hidden Markov model) recognizer and presents phonetic recognition results achieved with the system. As opposed to a conventional frame-based HMM, measurements in such a system are made on variable-duration segments. The key experimental result is that inclusion of measurements made beyond segment boundaries improves phonetic recognition performance significantly. On a set of nine male test speakers from the VOYAGER corpus, the system obtained a phonetic recognition accuracy of 59% (95% confidence interval of 53-65%) on a 39-class phonetic recognition task. Although little attempt was made to optimize system parameters, this result is competitive with existing systems of comparable complexity.<<ETX>>

Jeffrey N. Marcus | J. Marcus

[1] Victor W. Zue,et al. A variable duration acoustic segment HMM for hard-to-recognize words and phrases , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[2] K. Stevens. Evidence for the role of acoustic boundaries in the perception of speech sounds , 1981 .

[3] Hsiao-Wuen Hon,et al. Speaker-independent phone recognition using hidden Markov models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[4] Richard O. Duda,et al. Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5] Victor Zue,et al. Collection and analysis of spontaneous and read corpora for spoken language system development , 1990, ICSLP.

[6] James R. Glass. Finding acoustic regularities in speech: applications to phonetic recognition , 1988 .

[7] Jeffrey Neil Marcus. Word and subword modelling in a segment-based HMM word spotter using a data analytic approach , 1992 .

[8] Mari Ostendorf,et al. A stochastic segment model for phoneme-based continuous speech recognition , 1989, IEEE Trans. Acoust. Speech Signal Process..