Speech enhancement using blind source separation and two-channel energy based speaker detection
Speech enhancement using blind source separation and two-channel energy based speaker detection
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使用盲源分离和基于双通道能量的说话人检测进行语音增强
DOI：
10.1109/icassp.2003.1198923
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Te
中科院分区：
文献类型：
--
作者：
Erik M. Visser;Te
提出了一种结合时空信号处理方法的语音增强方案，用于非平稳噪声环境下的盲去噪。在第一阶段，使用盲源分离（BSS）算法将空间定位的点源从两个麦克风记录的噪声语音信号中分离出来，假设对涉及的源没有先验知识。在第二处理步骤中去除空间分布的背景噪声。这里，包含期望扬声器的BSS输出通道用时变维纳滤波器进行滤波。滤波器系数的噪声功率估计由期望的扬声器缺席时间间隔计算，该时间间隔仅通过比较来自BSS级的分离源信号的信号能量来确定。通过对含杂音的真实录音进行语音识别实验，并与传统的波束形成和单通道去噪技术进行了比较，证明了该方案的性能。
A speech enhancement scheme is presented integrating spatial and temporal signal processing methods for blind denoising in non stationary noise environments. In a first stage, spatially localized point sources are separated from noisy speech signals recorded by two microphones using a Blind Source Separation (BSS) algorithm assuming no a priori knowledge about the sources involved. Spatially distributed background noise is removed in a second processing step. Here, the BSS output channel containing the desired speaker is filtered with a time-varying Wiener filter. Noise power estimates for the filter coefficients are computed from desired speaker absent time-intervals identified by comparing only signal energy of separated source signals from the BSS stage. The scheme's performance is illustrated by speech recognition experiments on real recordings corrupted by babble noise and compared to conventional beamforming and single channel denoising techniques.