Voice enhancement method based on double-ear sound source positioning and deep learning in double-ear hearing aid

Abstract

A vice enhancement method based on double-ear sound source positioning and deep learning in a double-ear digital hearing aid belongs to the field of voice signal processing. Firstly a two-stage deep neural network is used for accurately positioning a target voice, and noise in a direction which is different from the direction of target voice is eliminated according to spatial filtering. By means of a deep learning model in which a time delay control bidirectional long-short term memory deep neural network and a classifier are combined, an extracted multi-resolution hearing cepstrum coefficientis used as a characteristic input. Through nonlinear processing capability of deep learning, each time frequency unit of the noise-containing voice is classified to a voice time frequency unit or noise time frequency unit. Finally a voice waveform combining algorithm is used for eliminating the noise in the direction which is same with that of the target voice. The algorithm eliminates the noisein the direction which is different from the direction of the target voice and eliminates the noise in the direction that is same with the target voice, and finally obtains the enhanced voice which satisfies speech intelligibility and comfort of a deaf person. All deep learning models utilize offline training, thereby satisfying a requirement for real-time performance.

Description

technical field [0001] The invention belongs to the technical field of speech signal processing, and relates to two key speech signal processing technologies of target speech localization and speech enhancement in digital hearing aids. Background technique [0002] Hearing impairment is a chronic disease that seriously affects the quality of human life. In the United States, the incidence of hearing loss in the elderly over the age of 65 is about 30% to 40%, in Canada it is 20%, in Europe it is 35%, and in my country it is 35%. And with the increase of age, the incidence rate increases sharply. At present, the total number of elderly people over the age of 60 in the world has reached 600 million, of which my country accounts for nearly 30%, and only 22.28% of the elderly in my country have hearing thresholds within the normal range. The development of hearing aids has brought good news to these hearing-impaired patients. Hearing aid is a device that amplifies sound to sup...

AI Technical Summary

Problems solved by technology

However, in the above speech enhancement algorithms based on deep learning, either directly use all the collected data as the input of deep learning, but this method is very complex and does not meet the real-time requirements of digital hearing aids. The characteristic parameters of the data are used as the input of deep learning, but the characteristic parameters extracted by this method cannot describe the characteristics of speech and noise well, and cannot improve the speech intelligibility and comfort of the deaf.

However, the self-learning ability of deep neural network is unmatched by other methods.

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