Reference : Nonlinear Real-Time Emulation of a Tube Amplifier with a Long Short Term Memory Neura...
Scientific congresses and symposiums : Poster
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/2268/227161
Nonlinear Real-Time Emulation of a Tube Amplifier with a Long Short Term Memory Neural-Network
English
[en] Emulation en temps réel d'un amplificateur à tube avec un réseau de neurones Long Short Term Memory (LSTM)
Schmitz, Thomas mailto [Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore) >]
Embrechts, Jean-Jacques mailto [Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Techniques du son et de l'image >]
14-May-2018
A0
Yes
No
International
144th convention of the audio engineering society
du 23 May to 26 May
Milan
Italy
[en] real time emulation ; neural network ; nonlinear model
[en] Numerous audio systems for musicians are expensive and bulky. Therefore, it could be advantageous to model
them and to replace them by computer emulation. Their nonlinear behavior requires the use of complex models.
We propose to take advantage of the progress made in the field of machine learning to build a new model for such
nonlinear audio devices (such as the tube amplifier). This paper specially focuses on the real-time constraints of the
model. Modifying the structure of the Long Short Term Memory neural-network has led to a model 10 times faster
while keeping a very good accuracy. Indeed, the root mean square error between the signal coming from the tube
amplifier and the output of the neural network is around 2%.
http://hdl.handle.net/2268/227161

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