A comparison of trajectory and mixture modeling in segment-based word recognition

Authors:
Ashvin Kannan;Mari Ostendorf
Affiliations:
Electrical, Computer and Systems Engineering, Boston University, Boston, MA;Electrical, Computer and Systems Engineering, Boston University, Boston, MA
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Year:
1993

Citing 2
Cited 0

Segment-based stochastic models of spectral dynamics for continuous speech recognition

Segment-based stochastic models of spectral dynamics for continuous speech recognition
Segregation of speakers for speech recognition and speaker identification

ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference

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Abstract

This paper presents a mechanism for implementing mixtures at a phone-subsegment (microsegment) level for continuous word recognition based on the Stochastic Segment Model (SSM). We investigate the issues that are involved in trade-offs between trajectory and mixture modeling in segment-based word recognition. Experimental results are reported on DARPA's speaker-independent Resource Management corpus.