The Research On Loudness Compensation Of Digital Hearing Aids

Digital hearing aid is an effective way for hearing impaired patients to improve their listeningcomprehension. Loudness compensation is the core technology of digital hearing aids. After fullyunderstanding the conventional method, this thesis proposed some improved ones. The main workincludes:Firstly, this thesis introduced the basic knowledge of voice, incentive model, channel model andradiation model. And then, compared the three basic methods of speech signal analysis, learned themechanisms of hearing impairment, and investigated the clinical hearing test method which iswidely used.Secondly, in order to improve the listening recognition of hearing-impaired patients with severeloss of high-frequency hearing, this thesis proposed a new method which uses frequencycompression and shift techniques for multi-channel loudness compensation. This method couldreduce the negative impact during conventional loudness compensation. At first, high frequencyportion of the voice signal is compressed and shifted to the target frequency band. Then, the signalis divided into four unequal size bands via Quadrature Mirror Filter Bank. According to differenthearing-impaired patients, the identity of the signal on each band is compensated and controlled. Atlast, the processed signal is reconstructed using perfect reconstruction filter banks. By using theproposed method, the identity of the signal is enhanced obviously and the voice is restricted withinearshot of the hearing-impaired listeners.Thirdly, a novel single-channel compression and amplification algorithm based onmulti-resolution wavelet is proposed in this paper. Multi-resolution wavelet is involved todecompose and reconstruct the signal’s spectrum, which can help to extract the envelope of thesignal spectrum. Then, calculate the required gain of each feature point based on the input-outputcurve. After that, the gain of the whole signal spectrum is obtained by using the interpolationalgorithm. The proposed algorithm shows fairly good performance in both stimulation andsubjective test. The experiment and simulation indicate that the proposed algorithm has highpractical value.