DiffVox: A Differentiable Model for Capturing and Analysing Professional
  Effects Distributions
This study introduces a novel and interpretable model, DiffVox, for matching
vocal effects in music production. DiffVox, short for ``Differentiable Vocal
Fx", integrates parametric equalisation, dynamic range control, delay, and
reverb with efficient differentiable implementations to enable gradient-based
optimisation for parameter estimation. Vocal presets are retrieved from two
datasets, comprising 70 tracks from MedleyDB and 365 tracks from a private
collection. Analysis of parameter correlations highlights strong relationships
between effects and parameters, such as the high-pass and low-shelf filters
often behaving together to shape the low end, and the delay time correlates
with the intensity of the delayed signals. Principal component analysis reveals
connections to McAdams' timbre dimensions, where the most crucial component
modulates the perceived spaciousness while the secondary components influence
spectral brightness. Statistical testing confirms the non-Gaussian nature of
the parameter distribution, highlighting the complexity of the vocal effects
space. These initial findings on the parameter distributions set the foundation
for future research in vocal effects modelling and automatic mixing. Our source
code and datasets are accessible at https://github.com/SonyResearch/diffvox.
6807f85efcd784a902c87126
Chin-Yun Yu
claimed_verified
2025-04-23T08:28:18.913Z
621d85a10e35b2fbbf3e6196
https://cdn-avatars.huggingface.co/v1/production/uploads/621d85a10e35b2fbbf3e6196/D6DMntYh-eV5fVef_Mx4Z.png
Chin-Yun Yu
user
yoyolicoris
6807f85efcd784a902c87127
Marco A. Martínez-Ramírez
6807f85efcd784a902c87128
Junghyun Koo
claimed_verified
2025-07-22T08:00:50.262Z
63f5c72fb607296857b14de7
/avatars/c4ae2f44e2f925ab9812ba9c046e53dd.svg
Junghyun (Tony) Koo
user
jhtonyKoo
6807f85efcd784a902c87129
Ben Hayes
6807f85efcd784a902c8712a
Wei-Hsiang Liao
6807f85efcd784a902c8712b
György Fazekas
6807f85efcd784a902c8712c
Yuki Mitsufuji
DiffVox: A Differentiable Model for Capturing and Analysing Professional
  Effects Distributions
This study introduces a novel and interpretable model, DiffVox, for matching
vocal effects in music production. DiffVox, short for ``Differentiable Vocal
Fx", integrates parametric equalisation, dynamic range control, delay, and
reverb with efficient differentiable implementations to enable gradient-based
optimisation for parameter estimation. Vocal presets are retrieved from two
datasets, comprising 70 tracks from MedleyDB and 365 tracks from a private
collection. Analysis of parameter correlations highlights strong relationships
between effects and parameters, such as the high-pass and low-shelf filters
often behaving together to shape the low end, and the delay time correlates
with the intensity of the delayed signals. Principal component analysis reveals
connections to McAdams' timbre dimensions, where the most crucial component
modulates the perceived spaciousness while the secondary components influence
spectral brightness. Statistical testing confirms the non-Gaussian nature of
the parameter distribution, highlighting the complexity of the vocal effects
space. These initial findings on the parameter distributions set the foundation
for future research in vocal effects modelling and automatic mixing. Our source
code and datasets are accessible at https://github.com/SonyResearch/diffvox.
DiffVox, a differentiable model, integrates vocal effects using gradient-based optimization for parameter estimation, analyzing their correlations and connections to timbre dimensions.
DiffVox differentiable implementations gradient-based optimisation parametric equalisation dynamic range control delay reverb principal component analysis timbre dimensions Gaussian nature