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Weighted Viterbi algorithm and state duration modelling for speech recognition in noise
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181)
A weighted Viterbi algorithm (HMM) is proposed and applied in combination with spectral subtraction and Cepstral Mean Normalization to cancel both additive and convolutional noises in speech recognition. The weighted Viterbi approach is compared and used in combination with state duration modelling. The results presented in this paper show that a proper weight on the information provided by static parameters can substantially reduce the error rate, and that the weighting procedure improves
doi:10.1109/icassp.1998.675363
dblp:conf/icassp/YomaMJ98
fatcat:oekauuj76fcwnh3kekn227743q