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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Hearing Aid Method by Equalizing Frequency Response of Phoneme Extracted from Human Voice

Author 1: Kohei Arai
Author 2: Takuto Konishi

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080713

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 7, 2017.

  • Abstract and Keywords
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Abstract: Hearing aid method by equalizing frequency response of phoneme which is extracted from human voice is proposed. One of the problems of the existing hearing aid is poor customization of the frequency response compensation. Frequency response characteristics are different by the person who need hearing aid. The proposed hearing aid is based on frequency response equalization by phoneme by phoneme. Frequency characteristics of phoneme are to be equalized. This is the specific feature of the proposed hearing aid method. Through experiments, it is found that the proposed hearing aid by phoneme is superior to the conventional hearing aid.

Keywords: Hearing aid; phoneme; frequency response; equalization filter; hidden markov model (HMM)

Kohei Arai and Takuto Konishi, “Hearing Aid Method by Equalizing Frequency Response of Phoneme Extracted from Human Voice” International Journal of Advanced Computer Science and Applications(IJACSA), 8(7), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080713

@article{Arai2017,
title = {Hearing Aid Method by Equalizing Frequency Response of Phoneme Extracted from Human Voice},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080713},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080713},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {7},
author = {Kohei Arai and Takuto Konishi}
}


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