基于小波變換和獨立分量分析的含噪混疊語音盲分離
Blind Separation of Noisy Speech Mixtures Based on Wavelet Transform and Independent Component Analysis
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摘要: 含噪混疊語音的分離是語音信號處理中的重要研究問題。該文針對語音信號的非平穩(wěn)特性與不同語音源之間的相互獨立性，提出用小波變換與獨立分量分析相結(jié)合的方法來進(jìn)行分離。首先利用小波變換分別對各含噪混疊語音進(jìn)行消噪，然后用獨立分量分析的方法對消噪后的混疊信號進(jìn)行分離，最后進(jìn)一步對分離信號作矢量歸一和再消噪處理，得到各個語音源信號的最終估計。仿真結(jié)果表明這種方法取得了很好的分離效果。
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關(guān)鍵詞:
- 語音分離;小波變換;獨立分量分析;噪聲消除
Abstract: A vital issue in speech processing is to extract source speeches from noisy mixtures. A method is presented based on wavelet transform and independent component analysis in this paper. Firstly, de-noise the noisy mixtures with discrete wavelet transform. Secondly, get them separated by independent component analysis. Finally, do the post-processing to the separated signals, then the estimated source speeches are got. Simulation results exhibit a high level of separating performance. -
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