3 citations · 3 across the 9 of their papers we have counts for
10 papers
Accelerating Automatic Differentiation of Direct Form Digital Filters
Chin-Yun Yu, György Fazekas
We introduce a general formulation for automatic differentiation through direct form filters, yielding a closed-form backpropagation that includes initial condition gradients. The…
Sound Matching an Analogue Levelling Amplifier Using the Newton-Raphson Method
Chin-Yun Yu, György Fazekas
Automatic differentiation through digital signal processing algorithms for virtual analogue modelling has recently gained popularity. These algorithms are typically more computatio…
Improving Inference-Time Optimisation for Vocal Effects Style Transfer with a Gaussian Prior
Chin-Yun Yu, Marco A. Martínez-Ramírez, Junghyun Koo +3
Style Transfer with Inference-Time Optimisation (ST-ITO) is a recent approach for transferring the applied effects of a reference audio to an audio track. It optimises the effect p…
DiffVox: A Differentiable Model for Capturing and Analysing Vocal Effects Distributions
Chin-Yun Yu, Marco A. Martínez-Ramírez, Junghyun Koo +4
This study introduces a novel and interpretable model, DiffVox, for matching vocal effects in music production. DiffVox, short for ``Differentiable Vocal Fx", integrates parametric…
Differentiable Time-Varying Linear Prediction in the Context of End-to-End Analysis-by-Synthesis
Chin-Yun Yu, György Fazekas
Training the linear prediction (LP) operator end-to-end for audio synthesis in modern deep learning frameworks is slow due to its recursive formulation. In addition, frame-wise app…
Time-of-arrival Estimation and Phase Unwrapping of Head-related Transfer Functions With Integer Linear Programming
Chin-Yun Yu, Johan Pauwels, György Fazekas
In binaural audio synthesis, aligning head-related impulse responses (HRIRs) in time has been an important pre-processing step, enabling accurate spatial interpolation and efficien…