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Musical-noise-free blind speech extraction integrating microphone array and iterative spectral subtraction

机译:集成麦克风阵列和迭代频谱减法的无音乐噪声盲语音提取

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摘要

In this paper, we propose a musical-noise-free blind speech extraction method using a microphone array for application to nonstationary noise. In our previous study, it was found that optimized iterative spectral subtraction (SS) results in speech enhancement with almost no musical noise generation, but this method is valid only for stationary noise. The proposed method consists of iterative blind dynamic noise estimation by, e.g., independent component analysis (ICA) or multichannel Wiener filtering, and musical-noise-free speech extraction by modified iterative SS, where multiple iterative SS is applied to each channel while maintaining the multichannel property reused for the dynamic noise estimators. Also, in relation to the proposed method, we discuss the justification of applying ICA to signals nonlinearly distorted by SS. From objective and subjective evaluations simulating a real-world hands-free speech communication system, we reveal that the proposed method outperforms the conventional methods.
机译:在本文中,我们提出了一种使用麦克风阵列的无音乐噪声的盲语音提取方法,用于非平稳噪声。在我们之前的研究中,发现优化的迭代频谱减法(SS)会导致语音增强,几乎不会产生音乐噪声,但是这种方法仅对平稳噪声有效。所提出的方法包括:通过独立分量分析(ICA)或多通道维纳滤波进行迭代盲动态噪声估计,以及通过改进的迭代SS提取无音乐噪声的语音,其中,在保持信道噪声的同时,对每个通道应用多个迭代SS多通道属性被重新用于动态噪声估计器。此外,相对于所提出的方法,我们讨论了将ICA应用于SS非线性失真信号的合理性。通过模拟真实世界的免提语音通信系统的主观和主观评估,我们发现所提出的方法优于传统方法。

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