The Effect of Noise on Deep Learning for Classification of Pathological Voice.

Journal: The Laryngoscope
PMID: 38280184

Abstract

OBJECTIVE: This study aimed to evaluate the significance of background noise in machine learning models assessing the GRBAS scale for voice disorders.

Authors

  • Koki Hasebe
    Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Shintaro Fujimura
    Department of Otolaryngology , Tenri Hospital, Tenri, Nara, Japan.
  • Tsuyoshi Kojima
    Department of Otolaryngology , Tenri Hospital, Tenri, Nara, Japan.
  • Keiichi Tamura
    Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Yoshitaka Kawai
    Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Yo Kishimoto
    Department of Otolaryngology - Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Koichi Omori
    Department of Otolaryngology-Head and Neck Surgery, Kyoto University, Kyoto, Japan.

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