A multilayer perceptron postprocessor to hidden Markov modeling for speech recognition

Authors:
Jin Guo;Chung Ho Lui
Affiliations:
Institute of Systems Science, National University of Singapore, Singapore;Institute of Systems Science, National University of Singapore, Singapore
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Year:
1993

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Abstract

In this paper, a new neural network postprocessor is introduced to enhance the classification capability of hidden Markov modeling for speech recognition. This postprocessor receives stimuli from not one but all word- HMMs for each word speech and does not require segmenting speech frames at subword level. A multilayer perceptron implementation has achieved 20% to 30% syllable error reduction in experiments reported here.