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- W1986237449 abstract "Abstract This paper presents an adaptation method of speech hidden Markov models (HMMs) for telephone speech recognition. Our goal is to automatically adapt the HMM parameters so that the adapted HMM parameters can match with the telephone environment. In this study, two kinds of transformation-based adaptations are investigated. One is the bias transformation and the other is the affine transformation. A Bayesian estimation technique which incorporates prior knowledge into the transformation is applied for estimating the transformation parameters. Experiments show that the proposed approach can be successfully employed for self adaptation as well as supervised adaptation. Besides, the performance of telephone speech recognition using Bayesian adaptation is shown to be superior to that using maximum-likelihood adaptation. The affine transformation is also demonstrated to be significantly better than the bias transformation." @default.
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- W1986237449 date "1997-09-01" @default.
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- W1986237449 title "Telephone speech recognition based on Bayesian adaptation of hidden Markov models" @default.
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- W1986237449 doi "https://doi.org/10.1016/s0167-6393(97)00033-2" @default.
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