关键词: 脉冲噪声, 语音增强, 卡尔曼滤波, AR模型, 滤波器组

Abstract: Speech enhancement aims at extracting clean speech from noisy speech. Traditional speech enhancement algorithms proposed for continuous noise can not work well when clean speech is polluted by impulsive noise. The feature of the distribution of impulsive noise in time domain has to be concerned for speech enhancement. This paper provided a new speech enhancement method for the removal of noise when clean speech is polluted by stationary impulsive noise. By analyzing the samples of impulsive noise and noisy speech, the method found the frequency band in which the energy of impulsive noise was most evident compared with the energy of noisy speech. Furthermore, filter banks were used in recognizing whether the speech frame was polluted. The method based on Kalman filtering removed impulsive noise from the polluted signal frame. Compared with the traditional algorithms based on Kalman filtering, the method also improved the process of the parameters estimation of Auto Regressive (AR) model. In some speech enhancement tests, speech was polluted by white impulsive noise or colored impulsive noise, the results show that the method has achieved an improved Signal-to-Noise Ratio (SNR) and removes impulsive noise even when the SNR of noisy speech is low.

Key words: impulse noise, speech enhancement, filter bank