title: DiffVox: A Differentiable Model for Capturing and Analysing Professional
    Effects Distributions
summary: 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.
paper_authors._id: 6807f85efcd784a902c87126
paper_authors.name: Chin-Yun Yu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-04-23T08:28:18.913Z
paper_authors._id: 621d85a10e35b2fbbf3e6196
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/621d85a10e35b2fbbf3e6196/D6DMntYh-eV5fVef_Mx4Z.png
paper_authors.fullname: Chin-Yun Yu
paper_authors.type: user
paper_authors.user: yoyolicoris
paper_authors._id: 6807f85efcd784a902c87127
paper_authors.name: Marco A. Martínez-Ramírez
paper_authors._id: 6807f85efcd784a902c87128
paper_authors.name: Junghyun Koo
paper_authors._id: 6807f85efcd784a902c87129
paper_authors.name: Ben Hayes
paper_authors._id: 6807f85efcd784a902c8712a
paper_authors.name: Wei-Hsiang Liao
paper_authors._id: 6807f85efcd784a902c8712b
paper_authors.name: György Fazekas
paper_authors._id: 6807f85efcd784a902c8712c
paper_authors.name: Yuki Mitsufuji
paper_title: DiffVox: A Differentiable Model for Capturing and Analysing Professional
    Effects Distributions
paper_summary: 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.
paper_ai_summary: DiffVox, a differentiable model, integrates vocal effects using gradient-based optimization for parameter estimation, analyzing their correlations and connections to timbre dimensions.
paper_ai_keywords: DiffVox differentiable implementations gradient-based optimisation parametric equalisation dynamic range control delay reverb principal component analysis timbre dimensions Gaussian nature