基于彩色特征的语音信号盲反卷积方法

F. Cong, Peng Jia, Shaoling Ji, Xizhi Shi, Zhenhai Wang, Chi Hau Chen
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引用次数: 1

摘要

盲问题中基于时间的卷积混合可以转化为基于频率的瞬时混合,因为时域的卷积运算对应于频率1的乘法。对整个语音信号进行分块,并对每个分块信号进行快速傅里叶变换(FFT),在频域构造新的彩色瞬时混合信号。利用二阶统计量(SOS),对彩色信号进行基于代价函数的盲分离,在每个频域分别计算未混合矩阵。因此,在时域中,对与不同频箱的未混合矩阵相关联的推断信号采用基于相关性的置换后进行反卷积。实验证明了该方法通过频域盲分离实现盲反卷积的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approach based on colored character to blind deconvolution for speech signals
The time-based convolutive mixing can be transformed to the frequency-based instantaneous mixing in blind problems as the convolution operation in time domain corresponds to a multiplication in frequency one. After performing blocks on the whole speech signal, and applying Fast Fourier Transform (FFT) on each blocked signal, the new colored instantaneous mixing signals in frequency domain are constructed. Making use of the Second Order Statistics (SOS), the unmixed matrices are respectively computed at each frequency bin by blind separation based on cost function which is aimed at colored signals. Thus, in time domain, deconvolution is performed after employing correlation-based permutation to the inferred signals which are associated with the unmixed matrices at different frequency bins. The experiment proves the effectiveness of the approach to blind deconvolution by blind separation in frequency domain.
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