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神经网络在语音信号消噪处理中的应用
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作者 龚文凌 王洪澄 《计算机应用与软件》 CSCD 北大核心 2005年第2期73-75,共3页
提出了一种利用神经网络进行语音信号消噪处理的新方法。在无噪和含噪条件下 ,提取语音信号的包络谱 ,用于BP神经网络的训练和识别 ,再叠加上原始语音信号的特征 ,最终达到语音信号消噪和提高可懂度的目的。
关键词 语音信号 消噪处理 神经网络 浊音信号 频谱减法
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Segregation of voiced and unvoiced components from residual of speech signal 被引量:1
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作者 JO Cheol-woo KIM Jae-hee 《Journal of Central South University》 SCIE EI CAS 2012年第2期496-503,共8页
In conventional source-filter models, voiced and unvoiced components were considered independently. However, in practice it was difficult to separate the source into two parts. An actual source consists of a mixture o... In conventional source-filter models, voiced and unvoiced components were considered independently. However, in practice it was difficult to separate the source into two parts. An actual source consists of a mixture of two sources and the ratio varies according to the content or the intention of speaker. It had been investigated to separate the voiced and unvoiced components for different source models. Source signals were modeled based on the residual signal measured from inverse filtering. Three different source models were assumed. The parameters of each model were optimized for the original speech signal using a genetic algorithm. The resulting parameters were compared in terms of the mel-cepstral distance to the original signal, the spectrogram and the spectral envelope from the synthesized signal. The optimization method achieves an improvement of 15% for the Klatt model, but there is little improvement in the modified residual case. 展开更多
关键词 voice source model SYNTHESIS optimization genetic algorithm
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