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Adaptation mode control with residual noise estimation for beamformer-based multi-channel speech enhancement

机译:具有残留噪声估计的自适应模式控制,用于基于波束形成器的多通道语音增强

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In this paper, we propose a new adaptation mode controller (AMC) for a generalized sidelobe canceller (GSC) having prior knowledge of the direction-of-arrival (DOA) of a desired speech source. In order to optimize the adaptation mode of a GSC, the residual noise remaining in the GSC output must be employed for adapting the AMC. The residual noise in the GSC output is estimated by using a short-time Fourier transform (STFT)-based Wiener filter, where a priori signal-to-noise ratio (SNR) and a posteriori target-to-non-target-directional signal ratio (TNR) are estimated based on a decision-directed approach and a DOA-based approach, respectively. The estimated residual noise is finally incorporated as a control parameter into the adaptive filters in the AMC. The performance of the proposed AMC is evaluated by measuring the perceptual evaluation of speech quality (PESQ) scores and cepstral distortion in car noise environments with SNRs from 0 to 20 dB. Experimental results show that the proposed AMC performs better than the conventional AMCs.
机译:在本文中,我们提出了一种新的自适应模式控制器(AMC),用于广义旁瓣抵消器(GSC),它具有所需语音源的到达方向(DOA)的先验知识。为了优化GSC的自适应模式,必须采用GSC输出中残留的残余噪声来自适应AMC。通过使用基于短时傅立叶变换(STFT)的Wiener滤波器估算GSC输出中的残留噪声,其中先验信噪比(SNR)和后验目标与非目标方向信号比率(TNR)分别基于决策导向方法和基于DOA的方法进行估算。最后,将估计的残留噪声作为控制参数合并到AMC中的自适应滤波器中。建议的AMC的性能通过在SNR为0至20 dB的汽车噪声环境中测量语音质量(PESQ)分数和倒谱失真的感知评估来评估。实验结果表明,提出的AMC的性能优于常规AMC。

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