A linear predictive HMM for vector-valued observations with applications to speech recognition
Authors:
- 1 February 1990
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Acoustics, Speech, and Signal Processing
- Vol. 38 (2) , 220-225
Abstract
The authors describe a new type of Markov model developed to account for the correlations between successive frames of a speech signal. The idea is to treat the sequence of frames as a nonstationary autoregressive process whose parameters are controlled by a hidden Markov chain. It is shown that this type of model performs better than the standard multivariate Gaussian HMM (hidden Markov model) when it is incorporated into a large-vocabulary isolated-word recognizer.<>Keywords
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