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Noise suppression method for body-conducted soft speech enhancement based on external noise monitoring

机译:基于外部噪声监测的人体传导软语音增强的噪声抑制方法

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This paper presents a novel approach to suppressing adverse effects of external noise on body-conducted soft speech for silent speech communication in noisy environments. Nonaudible murmur (NAM) microphone as one of the body-conductive microphones is capable of detecting very soft speech. However, body-conducted soft speech easily suffers from external noise owing to its faint volume. To address this issue, the proposed method additionally uses an air-conductive microphone to detect only an external noise signal and uses the detected external noise signal to suppress its effect on the body-conducted soft speech. A semi-blind source separation technique is app??ed to the proposed method for estimating a linear filter to suppress the noise components without voice activity detection. Experimental results demonstrate that the proposed method yields 10 dB SNR improvements in 80 dBA noisy conditions and also yields significant improvements in sound quality of body-conducted soft speech.
机译:本文提出了一种抑制外部噪声对身体对噪声环境中静音语音通信的不利影响的新方法。非吸华杂音(NAM)麦克风作为主体导电麦克风之一能够检测非常柔软的语音。然而,由于其微弱的体积,身体传导的软音容易遭受外部噪音。为了解决这个问题,所提出的方法另外使用空气导电麦克风来检测外部噪声信号,并使用检测到的外部噪声信号来抑制其对身体传导的软语音的影响。半盲源分离技术是应用程序??编辑用于估计线性滤波器以抑制没有语音活动检测的噪声分量的方法。实验结果表明,该方法在80 dBA嘈杂的条件下产生10 dB的SNR改进,并且还产生了对身体传导软言论的音质的显着改善。

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