首页> 外文会议>2nd IET International Conference on Intelligent Signal Processing 2015 >Performance improvement in single-channel blind separation with pseudo-stereo mixture using cochleagram representation based masks
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Performance improvement in single-channel blind separation with pseudo-stereo mixture using cochleagram representation based masks

机译:使用基于耳蜗图表示的蒙版伪立体声混合物在单通道盲分离中的性能改进

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A novel single-channel blind source separation (SCBSS) algorithm using Cochleagram-mask based technique is presented in this paper. The proposed system offers benefits such as resemblance of a stereo signal concept given by one microphone, independent of initialization and a priori knowledge of the sources, improved performance with sources which do not strictly satisfy the windowed-disjoint orthogonality (WDO) condition and reduced computational complexity without the need for iterative optimizations. The separation process comprises three steps: 1) estimation of source characteristics, where the source signals are modelled by the autoregressive process and 2) construction of masks using only the single-channel mixture 3) binary TF masks modification through cochleagram processing 4) improve separation depth through independent component analysis (ICA). Experiment results revealed at least 3dB signal to interference ratio comparing to previous systems [1].
机译:提出了一种基于耳蜗掩模技术的单通道盲源分离算法。所提出的系统具有以下优点:与一个麦克风给出的立体声信号概念相似,独立于信号源的初始化和先验知识,使用严格不满足窗口不相交正交性(WDO)条件的信号源提高了性能,并减少了计算量复杂性,无需迭代优化。分离过程包括三个步骤:1)估计源特性,其中源信号通过自回归过程建模; 2)仅使用单通道混合物构建掩模; 3)通过耳蜗图处理修改二进制TF掩模; 4)改善分离通过独立成分分析(ICA)进行深度分析。实验结果表明,与以前的系统相比,至少有3dB的信噪比[1]。

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