Research On Speech Enhancement Techniques Of Digital Hearing Aids

The main purpose of speech enhancement is to eliminate the noise in noisy speech, to extract more pure speech and it has great significance to improve the performance of digital hearing aids. The major study of this thesis is the speech enhancement technology of digital hearing aids. This thesis studies the speech enhancement based on a prior SNR estimation and the speech enhancement based on human auditory masking effect, and proposes the improved algorithms. The main work of the thesis includes the following aspects:First, this thesis studies the speech enhancement of digital hearing aids, and does research on the speech enhancement based on a prior SNR estimation and speech enhancement based on human auditory masking threshold. And then this thesis makes simulation and performance analysis on different algorithm. Therefore we find that the gain function value between adjacent frames changes rapidly, which leads to random spikes in enhanced speech spectrum and results in musical noise. The traditional spectral subtraction has a bad effect on initial speech enhancement, resulting in a large error in masking threshold which causes to calculate the spectral subtraction coefficient inaccuracy; so it reduces the perceptual of the speech enhancement.Second, in order to reduce the impact of musical noise, an improved algorithm that combines the adaptive a prior SNR estimation with gain function smoothing is proposed. This proposed algorithm uses the difference degree of noisy speech spectrum and noise spectrum estimated to smooth gain function. The simulation results show that the proposed method can make the slowly varying values of the gain function between adjacent frames; so that it can eliminate the random spikes, suppress the musical noise effectively.Third, this thesis conducts research on the human auditory masking effect, analyzes the method based on human auditory masking effect and proposes an improved algorithm. The improved spectral subtraction based on entropy is applied. And this thesis uses the initial enhancement speech to calculate the masking threshold and obtains the more accurate threshold. So we can use the threshold to adjust the spectral subtraction coefficient. The simulation results show that the proposed method can improve the perceptual of the speech enhancement effectively.