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Single-channel speech separation using phase-based methods

机译:使用基于相位的方法进行单通道语音分离

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摘要

This paper addresses the problem of singlechannel speech separation to extract and enhance the desired speech signal from mixed speech signals. We propose a new speech separation algorithm by utilizing both magnitude and phase information, which can be applied to multimedia mobile communication and navigation systems. Conventionally, phase information has been neglected in speech signal processing. However, in the proposed method, we formulate a probabilistic phasebased speech estimator based on zero-phase models to improve the speech separation performance. In the speech separation experiments, the proposed method is shown to improve speaker-to-interference ratio (SIR) by 2.2 dB compared to the system using magnitude models only. When only phase-based speech estimator is used for speech separation, the SIR was improved by 0.8 dB. This result justify that the proposed phase-based speech estimator achieves significant SIR improvement compared with the previous magnitude-based method1.
机译:本文解决了单通道语音分离问题,以从混合语音信号中提取和增强所需的语音信号。我们提出了一种利用幅度和相位信息的语音分离新算法,该算法可以应用于多媒体移动通信和导航系统。传统上,在语音信号处理中已经忽略了相位信息。然而,在提出的方法中,我们基于零相位模型制定了基于概率相位的语音估计器,以提高语音分离性能。在语音分离实验中,与仅使用幅度模型的系统相比,该方法可将说话者干扰比(SIR)提高2.2 dB。当仅基于相位的语音估计器用于语音分离时,SIR提高了0.8 dB。这一结果证明,与以前的基于幅度的方法相比,所提出的基于相位的语音估计器可实现显着的SIR改善。

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