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一种新的多通道混合语音时域盲分离算法 被引量：2

Time-domain Blind Source Separation Algorithm of Mixed Speech Based on Component Clustering and Reconstruction
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摘要 卷积混合语音进行盲源分离时,不能直接应用独立分量分析(ICA)算法。采用一种新的卷积混合语音模型,对多通道混合语音使用近来提出的时域EFICA算法进行盲分离,然后利用聚类和重构算法来恢复源信号。通过真实语音实验表明,提出的算法能有效地分离混合语音信号。 BBS（Blind Source Separation） of convolution-mixed audio can not be applied directly to ICA（Independent Component Analysis） algorithm. A new convolution-mixed mode of the speech signal is used. Mixed audio multi- channel are processed using the recently proposed time-domain EFICA, then algorithm of clustering and reconstruction is used to restore the signal source. The experiments show that the algorithm can effectively separate mixed speech signal by the really audio.
作者 陶玉福 刘庆华 黄斌 樊伟
机构地区 桂林电子科技大学信息与通信学院
出处 《电声技术》 2009年第7期60-62,72,共4页 Audio Engineering
基金 广西自然科学基金项目(0832007Z)
关键词 盲源分离 独立分量分析 聚类 重构 BSS ICA clustering reconstruction
分类号 TN912 [电子电信—通信与信息系统]
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参考文献9

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同被引文献16

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电声技术
2009年 第7期

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