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A SIGNAL-SEPARATION-BASED ARRAY POSTFILTER FOR DISTANT SPEECH RECOGNITION

机译:用于遥远语音识别的基于信号分离的阵列后滤波器

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In standard microphone array processing for distant speech recogni ?tion, the beamformed output is postfiltered to reduce residual noise. Postfiltering is usually performed through a Weiner filter whose parameters are estimated from both the beamformer output and the signals captured at the microphones themselves. Conventional postfiltering methods assume diffuse or incoherent noise at the various microphones in order to estimate these parameters. When the noise does not conform to this assumption they perform poorly. We propose an alternate postfiltering mechanism that attenuates noise by estimating and separating out the contributions of speech and noise explicitly. Experiments on a corpus of in-car two-channel recordings show that the proposed postfiltering algorithm outperforms conventional postfilters significantly under many noise conditions.
机译:在用于远处语音识别的标准麦克风阵列处理中,过滤的波束成形输出以降低残留噪声。后滤线通常通过Weiner滤波器进行,其参数由波束形成器输出估计和在麦克风本身捕获的信号。传统的后滤音方法假设在各种麦克风处的漫射或非混合噪声以估计这些参数。当噪音不符合这种假设时,它们的表现不佳。我们提出了一种替代的后滤音机制,通过估计和分离语音和噪声的贡献来衰减噪声。在汽车车内两沟道记录中的实验表明,在许多噪声条件下,所提出的后滤音算法显着优于传统的后滤池。

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