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DOI: 10.14569/IJARAI.2015.040604
PDF

Mobile Device Based Personalized Equalizer for Improving Hearing Capability of Human Voices in Particular for Elderly Persons

Author 1: Kohei Arai
Author 2: Takuto Konishi

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 4 Issue 6, 2015.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Mobile device based personalized equalizer for improving the hearing capability of human voices in particular for elderly persons are proposed. Through experiments, it is found that the proposed equalizer does work well for improving hearing capability by 2 to 55 % of voice Recognition success ratio. According to the investigation of the frequency component analysis and formant detections, most of the voice sounds have the formant frequencies for the first to third frequencies within the range of 3445 Hz. Therefore, a nonlinear equalizing multiplier is better to enhance the frequency components for the first to third formants in particular. The experimental results with the voice above input experiments show that a good Percent Correct Recognition: PCR is required for 0 to more than 8000 Hz of frequency components. Also, 8162 Hz cut off frequency would be better for both noise suppressions and keeping a good PCR

Keywords: Frequency response equalization; mobile devices; formount frequancy; hearing capability; hearing aids

Kohei Arai and Takuto Konishi, “Mobile Device Based Personalized Equalizer for Improving Hearing Capability of Human Voices in Particular for Elderly Persons” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(6), 2015. http://dx.doi.org/10.14569/IJARAI.2015.040604

@article{Arai2015,
title = {Mobile Device Based Personalized Equalizer for Improving Hearing Capability of Human Voices in Particular for Elderly Persons},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2015.040604},
url = {http://dx.doi.org/10.14569/IJARAI.2015.040604},
year = {2015},
publisher = {The Science and Information Organization},
volume = {4},
number = {6},
author = {Kohei Arai and Takuto Konishi}
}



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.

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