Assistive Listening System Using a Human-Like Auditory Processing Algorithm

  • Po-Hsun Sung
  • Jhing-Fa Wang
  • Hsien-Shun Kuo
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 298)


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.


Auditory processing wavelet transform coherent demodulation spectro-temporal modulation filter non-stationary signal cortical representation assistive listening speech enhancement 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Electrical EngineeringNational Cheng Kung UniversityTainanTaiwan
  2. 2.Department of Digital Multimedia DesignTajen UniversityPingtung CountyTaiwan

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