摘要
Auditory model has been applied to several aspects of speech signal processing field, and appears to be effective in performance. This paper presents the inverse transform of each stage of one widely used auditory model. First of all it is necessary to invert correlogram and reconstruct phase information by repetitious iterations in order to get auditory-nerve firing rate. The next step is to obtain the negative parts of the signal via the reverse process of the HWR (Half Wave Rectification). Finally the functions of inner hair cell/synapse model and Gammatone filters have to be inverted. Thus the whole auditory model inversion has been achieved. An application of noisy speech enhancement based on auditory model inversion algorithm is proposed. Many experiments show that this method is effective in reducing noise. Especially when SNR of noisy speech is low it is more effective than other methods. Thus this auditory model inversion method given in this paper is applicable to speech enhancement field.
Auditory model has been applied to several aspects of speech signal processing field, and appears to be effective in performance. This paper presents the inverse transform of each stage of one widely used auditory model. First of all it is necessary to invert correlogram and reconstruct phase information by repetitious iterations in order to get auditory-nerve firing rate. The next step is to obtain the negative parts of the signal via the reverse process of the HWR (Half Wave Rectification). Finally the functions of inner hair cell/synapse model and Gammatone filters have to be inverted. Thus the whole auditory model inversion has been achieved. An application of noisy speech enhancement based on auditory model inversion algorithm is proposed. Many experiments show that this method is effective in reducing noise. Especially when SNR of noisy speech is low it is more effective than other methods. Thus this auditory model inversion method given in this paper is applicable to speech enhancement field.
基金
This work was supported by the National Natural Science Foundation of China (6017016)the Open Project Foundation of Signal Processing Key Laboratory of Jiangsu (KJS010021).