5 citations · 10 across the 9 of their papers we have counts for
10 papers
SCRAPL: Scattering Transform with Random Paths for Machine Learning
Christopher Mitcheltree, Vincent Lostanlen, Emmanouil Benetos +1
The Euclidean distance between wavelet scattering transform coefficients (known as paths) provides informative gradients for perceptual quality assessment of deep inverse problems…
Modulation Discovery with Differentiable Digital Signal Processing
Christopher Mitcheltree, Hao Hao Tan, Joshua D. Reiss
Modulations are a critical part of sound design and music production, enabling the creation of complex and evolving audio. Modern synthesizers provide envelopes, low frequency osci…
Neutone SDK: An Open Source Framework for Neural Audio Processing
Christopher Mitcheltree, Bogdan Teleaga, Andrew Fyfe +4
Neural audio processing has unlocked novel methods of sound transformation and synthesis, yet integrating deep learning models into digital audio workstations (DAWs) remains challe…
Differentiable All-pole Filters for Time-varying Audio Systems
Chin-Yun Yu, Christopher Mitcheltree, Alistair Carson +3
Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers. However, their recursive structure imp…
Modulation Extraction for LFO-driven Audio Effects
Christopher Mitcheltree, Christian J. Steinmetz, Marco Comunità +1
Low frequency oscillator (LFO) driven audio effects such as phaser, flanger, and chorus, modify an input signal using time-varying filters and delays, resulting in characteristic s…
SerumRNN: Step by Step Audio VST Effect Programming
Christopher Mitcheltree, Hideki Koike
Learning to program an audio production VST synthesizer is a time consuming process, usually obtained through inefficient trial and error and only mastered after years of experienc…