Word and subword modelling in a segment-based HMM word spotter using a data analytic approach
Word and subword modelling in a segment-based HMM word spotter using a data analytic approach
A variable duration acoustic segment HMM for hard-to-recognize words and phrases
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
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In this paper, we describe a segment-based HMM recognizer and present 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.