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Acoustic estimation of voice roughness.

Andrey Anikin1

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Standardized methods for measuring vocal roughness are crucial for consistent research. New algorithms estimate roughness from modulation spectra, explaining 50% of listener rating variance and aiding communication analysis.

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Area of Science:

  • Acoustics
  • Psychoacoustics
  • Bioacoustics

Background:

  • Vocal roughness is a key perceptual characteristic in human and animal communication.
  • It plays a role in social dominance and urgent signals like screams.
  • Standardized measurement methods are needed for reliable roughness research.

Purpose of the Study:

  • To review existing literature on roughness estimation.
  • To present and validate new algorithms for acoustic roughness measurement.
  • To provide standardized tools for roughness analysis in vocalizations.

Main Methods:

  • Literature review of roughness estimation techniques.
  • Perceptual experiments with 602 human vocal samples rated by 162 listeners.
  • Development and optimization of two algorithms using modulation spectra (gammatone/Butterworth filters and Short-Time Fourier transform).

Main Results:

  • Two acoustic algorithms were developed to estimate vocal roughness.
  • Both algorithms explained approximately 50% of the variance in human listener ratings.
  • The optimal modulation frequency range for roughness perception was identified as [50, 200] Hz.

Conclusions:

  • The developed algorithms provide a standardized and objective method for measuring vocal roughness.
  • Modulation and roughness spectrograms can visualize roughness dynamics.
  • The algorithms are available in the open-source R library soundgen, with data publicly accessible for benchmarking.