Speech Enhancement Based on Auto Gain Control

We propose a new method of speech enhancement based on auto gain control (AGC) using two channel inputs to deal with transient noises. Auto gain control is considered to be relatively ineffective for reducing noises that are superimposed on speech. Nevertheless, it offers advantages for addressing problems posed by musical noise and spectral distortion. This method combines two operations for obtaining accurate gain. One is spectral subtraction for two-channel input (2chSS); the other is self-offset of the noise with pre-whitening. This study also addresses a coherence based post-filter to reduce uncorrelated noise components among channels. The proposed method is evaluated in experiments across three noise conditions in which (i) impulsive noises, (ii) stationary car noise, and (iii) speech noise are present, respectively. Objective measures and spectrograms demonstrate marked improvements over other two-microphone based methods, but subjective preference tests reveal that the proposed method is less preferred than the equivalent of a nonprocessed signal in the case of stationary car noise (ii). The performance of the proposed method and the conventional 2chSS were even in the case of speech noise (iii). These results of subjective tests reflect some disadvantages of the AGC processing. Those drawbacks involve degradation of noise consistency in stationary noise conditions and residual noises in desired speech segments. Nevertheless, subjective tests in the case of noise (i) demonstrate that the proposed method is the most preferred among the methods compared here. The effectiveness of the proposed method is confirmed particularly for this noise condition