Research on Speech Enhancement Algorithm Based on Modified Wavelet Threshold Function

Threshold function plays an important role in speech enhancement using wavelet threshold, which directly determines the effect of speech enhancement. However, the existing threshold functions have various deficiencies, such as incontinuity and computing complex and the fixed functional form in different decomposition levels. In order to resolve the above-mentioned problems, a modified continuous threshold function was proposed, which can adjust automatically with the change of wavelet decomposition scale and have adjusted parameters. Wavelet coefficients of the noisy speech signal have been processed using the modified threshold function in wavelet domain, and the optimal solution was acquired by genetic algorithm. Furthermore, the processed optimal wavelet coefficients were utilized to reconstruct the enhancement speech signal .Experiments have been carried out in simulated and real environments. The modified threshold function had advantage over the traditional one in three aspects of signal-to-noise（SNR）and mean-square error（MSE） and subjective evaluation of speech signal . Experimental results reveal that the speech enhancement algorithm using modified threshold function has effectively improved the intelligibility and quality of de-noised speech signal.