7 papers
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…
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…
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…
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…
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…
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…