A variable duration acoustic segment HMM for hard-to-recognize words and phrases

Authors:
J. N. Marcus;V. W. Zue
Affiliations:
Lab. for Comput. Sci., MIT, Cambridge, MA, USA;Lab. for Comput. Sci., MIT, Cambridge, MA, USA
Venue:
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Year:
1991

Citing 0
Cited 2

A multi-resolution hidden Markov model using class-specific features

IEEE Transactions on Signal Processing
Phonetic recognition in a segment-based HMM

ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II

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Abstract

The authors consider how hidden Markov models (HMM) can be modified to accommodate a segment-based representation, and how word and subword models can be combined to improve recognition performance. The investigation is conducted within the context of a system that attempts to spot confusable words and phrases in the VOYAGER continuous speech corpus. Specifically, the authors describe how segments of varying duration are determined such that measurements for estimating the model parameters can be made on these segments. The word-spotting system is also described in detail.