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<p>The assessment of voice quality plays a critical role in the clinical evaluation of hoarseness. However, no study has established a highly accurate method for the auditory–perceptual judgment of vocal roughness, which is one of the major components of hoarseness. In this study, we developed a multivariate acoustic model for quantifying vocal roughness using a tailored fundamental frequency (<i>f</i><sub><i>o</i></sub>) estimation algorithm. The newly devised parameters enabled the classification and quantification of subharmonics, a key component of rough voice. Furthermore, we introduce the acoustic roughness index (ARI), a predictive acoustic model that integrates these parameters with existing acoustic parameters. The ARI demonstrates high diagnostic accuracy and a strong correlation with auditory–perceptual roughness, establishing it as a robust index for the evaluation of vocal roughness.</p>

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A multivariate model incorporating subharmonic measurements for evaluating vocal roughness

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月20日

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  • Itsuki Kitayama,
  • Kiyohito Hosokawa,
  • Shinobu Iwaki,
  • Misao Yoshida,
  • Akira Miyauchi,
  • Kenji Aruga,
  • Takanari Kawabe,
  • Toshihiro Kishikawa,
  • Hidenori Tanaka,
  • Takeshi Tsuda,
  • Takashi Sato,
  • Yukinori Takenaka,
  • Makoto Ogawa,
  • Hidenori Inohara

摘要

The assessment of voice quality plays a critical role in the clinical evaluation of hoarseness. However, no study has established a highly accurate method for the auditory–perceptual judgment of vocal roughness, which is one of the major components of hoarseness. In this study, we developed a multivariate acoustic model for quantifying vocal roughness using a tailored fundamental frequency (fo) estimation algorithm. The newly devised parameters enabled the classification and quantification of subharmonics, a key component of rough voice. Furthermore, we introduce the acoustic roughness index (ARI), a predictive acoustic model that integrates these parameters with existing acoustic parameters. The ARI demonstrates high diagnostic accuracy and a strong correlation with auditory–perceptual roughness, establishing it as a robust index for the evaluation of vocal roughness.