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Hybrid approach to speech recognition using hidden Markov models and Markov chains

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1 Author(s)
J. Dai ; Robert Gordon Univ., Aberdeen, UK

The paper presents a hybrid of a hidden Markov model and a Markov chain model for speech recognition. In this hybrid, the hidden Markov model is concerned with the time-varying property of spectral features, while the Markov chain accounts for the interdependence of spectral features. The log-likelihood scores of the two models, with respect to a given utterance, are combined by a postprocessor to yield a combined log-likelihood score for word classification. Experiments on speaker-independent and multispeaker isolated English alphabet recognition show that the hybrid outperformed both the hidden Markov model and the Markov chain model in terms of recognition

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IEE Proceedings - Vision, Image and Signal Processing  (Volume:141 ,  Issue: 5 )