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| Nonlinear Statistical Matching for Subband Robust Speech Recognition |
| Sun Wei; Wu Zhen-yang; Liu Hai-bin |
| Dept of Radio Engineering, Southeast University, Nanjing 210096, China |
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Abstract The performance of the speech recognition systems is deteriorated dramatically under noise condition for variation of speech signal. According to the auditory tests, this paper proposes a new nonlinear sub-band Maximum A Posteriori (MAP)statistical matching algorithm based on the independent sub-band analysis. According to the perception of human’s ear and noise feature of different frequency-bands, the algorithm compensates the effects of noise with statistical matching, MAP estimation and HMM/MLP nonlinear mapping. The test shows that the proposed algorithm improves the recognition performance notably under noise condition.
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Received: 05 August 2004
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2006, Vol. 28 
