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dc.contributor.authorYu, C-Y
dc.contributor.authorMitcheltree, C
dc.contributor.authorCarson, A
dc.contributor.authorBilbao, S
dc.contributor.authorReiss, J
dc.contributor.authorFazekas, G
dc.contributor.authorInternational Conference on Digital Audio Effects 2024
dc.date.accessioned2024-07-09T10:52:06Z
dc.date.available2024-05-08
dc.date.available2024-07-09T10:52:06Z
dc.date.issued2024
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/97933
dc.description.abstractInfinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers. However, their recursive structure impedes end-toend training of these systems using automatic differentiation. Although non-recursive filter approximations like frequency sampling and frame-based processing have been proposed and widely used in previous works, they cannot accurately reflect the gradient of the original system. We alleviate this difficulty by reexpressing a time-varying all-pole filter to backpropagate the gradients through itself, so the filter implementation is not bound to the technical limitations of automatic differentiation frameworks. This implementation can be employed within audio systems containing filters with poles for efficient gradient evaluation. We demonstrate its training efficiency and expressive capabilities for modelling real-world dynamic audio systems on a phaser, time-varying subtractive synthesiser, and feed-forward compressor. We make our code and audio samples available and provide the trained audio effect and synth models in a VST plugin1 .en_US
dc.titleDifferentiable All-pole Filters for Time-varying Audio Systemsen_US
dc.typeConference Proceedingen_US
pubs.notesNot knownen_US
pubs.publication-statusAccepteden_US
dcterms.dateAccepted2024-05-08
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderNeural audio synthesis with expressiveness control::Engineering and Physical Sciences Research Councilen_US
qmul.funderNeural audio synthesis with expressiveness control::Engineering and Physical Sciences Research Councilen_US
rioxxterms.funder.projectb215eee3-195d-4c4f-a85d-169a4331c138en_US


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