Shunta Ishii, T. Toda, H. Saruwatari, S. Sakti, Satoshi Nakamura
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Blind noise suppression for Non-Audible Murmur recognition with stereo signal processing
In this paper, we propose a blind noise suppression method for Non-Audible Murmur (NAM) recognition. NAM is a very soft whispered voice detected with NAM microphone, which is one of the body-conductive microphones. Due to its recording mechanism, the detected signal suffers from noise caused by speaker's movements. In the proposed method using a stereo signal detected with two NAM microphones, the noise is estimated with blind source separation, and then, spectral subtraction is performed in each channel to reduce the noise. Moreover, channel selection is performed frame by frame to generate less distorted monaural NAM signal. Experimental results show that 1) word accuracy in large vocabulary continuous NAM recognition is degraded from 69.2% to 53.6% by the noise and 2) it is significantly recovered to 63.3% in a simulated situation and 58.6% in a real situation with the proposed method.
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