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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Assistive Listening System Using a Human-Like Auditory Processing Algorithm
verfasst von : Po-Hsun Sung, Jhing-Fa Wang, Hsien-Shun Kuo
Erschienen in: Intelligent Data analysis and its Applications, Volume II
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Enhancing the quality of hearing perception in noisy environments plays a significant role to improve life quality of elderly persons and hearing impaired people. Accordingly, this study presents a human-like auditory processing (HAP) algorithm to enhance the speech signal in low signal-to-noise ratio (SNR) and non-stationary noise environments. The proposed algorithm comprises two modules, namely Cochlear Wavelet Transform (CWT) and AM-FM Demodulation (AFD); mimicking the human peripheral auditory processing system and the human cortical auditory processing system, respectively. The performance of the proposed HAP algorithm is evaluated in accordance with the ITU Perceptual Evaluation of Speech Quality (PESQ) standard. The results show that the proposed algorithm improves the speech quality by 16.9 % on average. In the other words, the algorithm has significant potential for assistive listening in noisy environments.