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Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/1119

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Title: Connectionist probability estimators in HMM speech recognition
Authors: Renals, Steve
Morgan, Nelson
Bourlard, Herve
Cohen, Michael
Franco, Horacio
Issue Date: Jan-1994
Citation: IEEE Trans. on Speech and Audio Processing (1994) 2, 161-175.
Publisher: IEEE Signal Processing Society
Abstract: The authors are concerned with integrating connectionist networks into a hidden Markov model (HMM) speech recognition system. This is achieved through a statistical interpretation of connectionist networks as probability estimators. They review the basis of HMM speech recognition and point out the possible benefits of incorporating connectionist networks. Issues necessary to the construction of a connectionist HMM recognition system are discussed, including choice of connectionist probability estimator. They describe the performance of such a system using a multilayer perceptron probability estimator evaluated on the speaker-independent DARPA Resource Management database. In conclusion, they show that a connectionist component improves a state-of-the-art HMM system.
URI: Digital Object Identifier 10.1109/89.260359
http://ieeexplore.ieee.org/
http://hdl.handle.net/1842/1119
ISSN: 1063-6676
Appears in Collections:CSTR publications

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