activity
20242026
most citedSample Rate Independent Recurrent Neural Networks for Audio Effects Processing

1 citations · 1 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SD2026

Explicit and Stable Pseudospectral Time-Domain Method for the Föppl-von Kármán Equations

Victor Zheleznov, Stefan Bilbao

Modal synthesis is a widely-used technique for simulation of musical instrument dynamics. In the linear case, a modal decomposition leads to an uncoupled system of damped and force…

cs.SD2026

Stable Differentiable Modal Synthesis for Learning Nonlinear Dynamics

Victor Zheleznov, Stefan Bilbao, Alec Wright +1

Modal methods are a long-standing approach to physical modelling synthesis. Extensions to nonlinear problems are possible, leading to coupled nonlinear systems of ordinary differen…

eess.AS2026

Gradient-based Optimisation of Modulation Effects

Alistair Carson, Alec Wright, Stefan Bilbao

Modulation effects such as phasers, flangers and chorus effects are heavily used in conjunction with the electric guitar. Machine learning based emulation of analog modulation unit…

eess.AS2025

Anti-aliasing of neural distortion effects via model fine tuning

Alistair Carson, Alec Wright, Stefan Bilbao

Neural networks have become ubiquitous with guitar distortion effects modelling in recent years. Despite their ability to yield perceptually convincing models, they are susceptible…

cs.SD2025

Learning Nonlinear Dynamics in Physical Modelling Synthesis using Neural Ordinary Differential Equations

Victor Zheleznov, Stefan Bilbao, Alec Wright +1

Modal synthesis methods are a long-standing approach for modelling distributed musical systems. In some cases extensions are possible in order to handle geometric nonlinearities. O…

eess.AS2025

Resampling Filter Design for Multirate Neural Audio Effect Processing

Alistair Carson, Vesa Välimäki, Alec Wright +1

Neural networks have become ubiquitous in audio effects modelling, especially for guitar amplifiers and distortion pedals. One limitation of such models is that the sample rate of…

eess.AS2024

Interpolation Filter Design for Sample Rate Independent Audio Effect RNNs

Alistair Carson, Alec Wright, Stefan Bilbao

Recurrent neural networks (RNNs) are effective at emulating the non-linear, stateful behavior of analog guitar amplifiers and distortion effects. Unlike the case of direct circuit…

eess.AS2024★ 1 cited

Sample Rate Independent Recurrent Neural Networks for Audio Effects Processing

Alistair Carson, Alec Wright, Jatin Chowdhury +2

In recent years, machine learning approaches to modelling guitar amplifiers and effects pedals have been widely investigated and have become standard practice in some consumer prod…

eess.AS2024

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…