Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

Journal: Ear and hearing
Published Date: Jan 1, 2018

Abstract

OBJECTIVE: We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients.

Authors

  • Ying-Hui Lai
  • Yu Tsao
  • Xugang Lu
    National Institute of Information and Communications Technology, Japan.
  • Fei Chen
    Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Yu-Ting Su
  • Kuang-Chao Chen
    Department of Otolaryngology, Far Eastern Memorial Hospital, New Taipei, Taiwan.
  • Yu-Hsuan Chen
    Department of Chemical and Materials Engineering, National Central University 300 Zhongda Road, Zhongli District, Taoyuan City 320317, Taiwan R.O.C.
  • Li-Ching Chen
    Department of Otolaryngology, Cheng Hsin General Hospital, Taipei, Taiwan.
  • Lieber Po-Hung Li
    Department of Otolaryngology, Cheng Hsin General Hospital, Taipei, Taiwan.
  • Chin-Hui Lee
    School of Electrical and Computer Engineering, Georgia Institute of Technology, Georgia, USA.

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