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A signal subspace tracking algorithm for microphone array processing of speech

机译:用于语音麦克风阵列处理的信号子空间跟​​踪算法

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摘要

This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our objective is to enhance near-field speech signals by reducing multipath and reverberation. In real applications such as speech acquisition in acoustic environments, sources do not propagate along known and direct paths. Particularly in hands-free telephony, we have to deal with undesired propagation phenomena such as reflections and reverberation. Prior methods developed adaptive microphone arrays for noise reduction after a time delay compensation of the direct path. This simple synchronization is insufficient to produce an acceptable speech quality, and makes adaptive beamforming unsuitable. We prove the identification of source-to-array impulse responses to be possible by subspace tracking. We consequently show the advantage of treating synchronization as a matched filtering step. Speech quality is indeed enhanced at the output by the suppression of reflections and reverberation (i.e., dereverberation), and efficient adaptive beamforming for noise reduction is applied without risk of signal cancellation. Evaluations confirm the performance achieved by the proposed algorithm under real conditions.
机译:本文提出了一种使用带有信号子空间跟​​踪的匹配滤波器的自适应麦克风阵列波束成形方法。我们的目标是通过减少多径和混响来增强近场语音信号。在诸如声音环境中的语音采集之类的实际应用中,源不会沿已知路径和直接路径传播。特别是在免提电话中,我们必须处理不希望的传播现象,例如反射和混响。先前的方法开发了自适应麦克风阵列,用于在直接路径的时间延迟补偿之后降低噪声。这种简单的同步不足以产生可接受的语音质量,并且使自适应波束成形不合适。我们证明通过子空间跟踪可以识别源到阵列的脉冲响应。因此,我们显示了将同步视为匹配过滤步骤的优势。实际上,通过抑制反射和混响(即去混响),可以在输出端提高语音质量,并且可以应用有效的自适应波束形成来降低噪声,而不会产生信号消除的风险。评估证实了该算法在真实条件下的性能。

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