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Study on the Chinese continuous speech recognition under noise environments based on PCANN/HMM

机译:基于PCANN / HMM的噪声环境下的中文连续语音识别研究

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This paper presents a method to improve the noise robustness of Chinese continuous speech recognition system based on the PCANN/HMM hybrid structure. By using the principal components combined by successive multi-frames as the input of HMM, it introduces the dependency between frames and also reduces the noise effectively. And in this paper, we also improve the traditional spectral subtraction method. Experimental results demonstrate the efficiency of the new algorithms in Chinese continuous speech recognition under high noisy environments.
机译:本文提出了一种基于PCANN / HMM混合结构的中文连续语音识别系统的噪声鲁棒性提高方法。通过将连续的多帧组合的主成分用作HMM的输入,它引入了帧之间的依赖性,并且还有效地降低了噪声。并且在本文中,我们还改进了传统的光谱减法方法。实验结果证明了新算法在高噪声环境下对中文连续语音识别的有效性。

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