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KMID : 0917520040110040053
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Journal of Speech Sciences
2004 Volume.11 No. 4 p.53 ~ p.66
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IMM Algorithm with NPHMM for Speech Enhancement
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Lee Ki-Yong
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Abstract
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The nonlinear speech enhancement method with interactive parallel-extended Kalman filter is applied to speech contaminated by additive white noise. To represent the nonlinear and nonstationary nature of speech. we assume that speech is the output of a nonlinear prediction HMM (NPHMM) combining both neural network and HMM. The NPHMM is a nonlinear autoregressive process whose time-varying parameters are controlled by a hidden Markov chain. The simulation results shows that the proposed method offers better performance gains relative to the previous results [6] with slightly increased complexity.
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KEYWORD
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Nonlinear speech enhancement, Parallel-extended Kalman filter, Nonlinear prediction HMM, Neural network
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