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Voice Activity Detection using Microphone Array

机译:语音活动检测使用麦克风阵列

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It is useful to decide whether the microphone signal includes a target speech or not at a temporal moment because the process called the voice activity detection (VAD) can reduce any redundant efforts made for the speech coding or the speech recognition, or it can help provide more accurate noise estimation for the speech enhancement. The detection of speech or non-speech in a frame has been simply done by observing the variance of its energy level, zero crossing rate or periodicity. In this occasion, however, the detection error increases exponentially as much as the background noise is added up. Unvoiced fricative sounds which have low energy with being distributed over widebands are more vulnerable to the background noise than any other phonemes are. It is proposed in this literature that voice activity can be detected more robustly in noisy environment by observing the subband power ratio of the noisy speech and its beamformed signal. Also, it is shown to be effective in the fricatives than in the vowels. Whatsoever, this method guarantees much better performance than single microphone VADs when the noise is obviously reduced by beamforming.
机译:决定麦克风信号是否包括目标语音是有用的,因为称为语音活动检测(VAD)的过程可以减少用于语音编码或语音识别的任何冗余工作,或者它可以提供帮助语音增强更准确的噪声估计。通过观察其能级,过零率或周期性的方差来简单地完成帧中的语音或非语音的检测。然而,在这种情况下,检测误差随着背景噪声的增加而呈指数级增大。具有低能量的无声的摩擦声音与宽带分布的低能量更容易受到背景噪音的影响,而不是任何其他音素。在该文献中提出,通过观察噪声语音的子带功率比和其波束成形信号的子带功率比,可以在噪声环境中更稳健地检测语音活动。此外,它显示在玻璃瓶中的有效性而不是元音。无论如何,当噪声通过波束成形明显降低时,这种方法可以保证比单个麦克风VAD更好的性能。

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