DiffVox: A Differentiable Model for Capturing and Analysing Professional
  Effects Distributions
Authors: name: Chin-Yun Yu, name: Marco A. Martínez-Ramírez, name: Junghyun Koo, name: Ben Hayes, name: Wei-Hsiang Liao, name: György Fazekas, name: Yuki Mitsufuji
Organization: Sony

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.