Speech Enhancement Denoising Algorithm Based on Parameters Estimation and Perception Improvement

In order to enhance the whole quality of single channel speech enhancement denoising algorithm, both noise reducing and speech perception are considered to improve the traditional speech enhancement algorithm and many kinds of processing methods are taken to achieve the best optimization effect. Firstly, in the view of parameters estimation, spectrum smoothing algorithm based on weak speech presence is added to the soft decision method based on fixed prior signal-to-noise ratio in order to solve the problem of noise spectrum overestimation. Moreover, the smoothing parameter is dynamically controlled by the speech presence probability in order to enhance the tracing effect of prior signal-to-noise ratio. Secondly, in the view of the speech perception improvement, the harmonic reconstruction method is used to reconstruct the harmonic components in high frequencies of speech section. Phase compensation method and gain smoothing method are also employed to remove the annoying musical noise in speech and silence segment. The experimental results show that compared with the traditional algorithm, the proposed algorithm obtains good performance in both denoising effect and speech quality by introducing parameter estimation improvement module and perceived quality improvement module, and it is suitable for many kinds of noise environment and signal-to-noise ratio conditions.