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Acoustic estimation of voice roughness.
1Division of Cognitive Science, Department of Philosophy, Lund University, Box 192, SE- 221 00, Lund, Sweden. andrey.anikin@lucs.lu.se.
Attention, Perception & Psychophysics
|April 28, 2025
Summary
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.
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.
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