Modelling context dependency in acoustic-phonetic and lexical representations

Authors:
Michael Phillips;James Glass;Victor Zue
Affiliations:
-;-;-
Venue:
HLT '91 Proceedings of the workshop on Speech and Natural Language
Year:
1991

Citing 4
Cited 2

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A tree-trellis based fast search for finding the N Best sentence hypotheses in continuous speech recognition

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Context dependent vector quantization for continuous speech recognition

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

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Abstract

In 1989, our group first reported on the development of SUMMIT, a segment-based speaker-independent continuous-speech recognition system [13]. The initial version of SUMMIT made use of fairly simple context-independent models for the lexical labels. Recently, we have begun to incorporate more complex models of lexical labels that take into account a variety of contextual factors. These changes, along with an improved corrective training procedure for adapting pronunciation are weights and a larger set of training data, have resulted in the reduction of error rate by almost a factor of two on the Resource Management task.