Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Picture Segmentation by a Tree Traversal Algorithm
Journal of the ACM (JACM)
Improvements in the stochastic segment model for Phoneme recognition
HLT '89 Proceedings of the workshop on Speech and Natural Language
Integration of diverse recognition methodologies through reevaluation of N-best sentence hypotheses
HLT '91 Proceedings of the workshop on Speech and Natural Language
A dynamical system approach to approach to continuous recognition
HLT '91 Proceedings of the workshop on Speech and Natural Language
Speaker-independent phone recognition using BREF
HLT '91 Proceedings of the workshop on Speech and Natural Language
Experiments on speaker-independent phone recognition using BREF
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
The general use of tying in phoneme-based HMM speech recognisers
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
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In this paper we present methods for reducing the computation time of joint segmentation and recognition of phones using the Stochastic Segment Model (SSM). Our approach to the problem is twofold: first, we present a fast segment classification method that reduces computation by a factor of 2 to 4, depending on the confidence of choosing the most probable model. Second, we propose a Split and Merge segmentation algorithm as an alternative to the typical Dynamic Programming solution of the segmentation and recognition problem, with computation savings increasing proportionally with model complexity. Even though our current recognizer uses context-independent phone models, the results that we report on the TIMIT database for speaker independent joint segmentation and recognition are comparable to that of systems that use context information.