This is a curated list of papers related to neural net/machine learning applications in Audio Digital Signal Processing. The purpose of it is to help find useful pieces of information for newcomers
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COMMUNITYRTNeural: Fast Neural Inferencing for Real-Time Systems- 2021, Jatin Chowdhury -
Real-Time Modeling of Audio Distortion Circuits with Deep Learning- 2019, by Damskägg, Eero-Pekka; Juvela, Lauri; Välimäki, Vesa -
Real-time guitar amplifier emulation with deep learning- 2020, by Wright, Alec; Damskägg, Eero Pekka; Juvela, Lauri; Välimäki, Vesa -
Perceptual Loss Function for Neural Modelling of Audio Systems- 2020, by Wright, Alec; Välimäki, Vesa -
Neural Modelling of LFO Modulated Time Varying Effects- 2020, by Wright, Alec; Välimäki, Vesa -
Real-time black-box modelling with recurrent neural networks- 2019, by Wright, Alec; Damskägg, Eero-Pekka; Välimäki, Vesa -
Deep Learning for Black-Box Modeling of Audio Effects- 2020, by Marco A. Martínez Ramírez, Emmanouil Benetos and Joshua D. Reiss -
Modelling of nonlinear state-space systems using a deep neural network- 2019, by Julian D. Parker, Fabián Esqueda, André Bergner -
DDSP: Differentiable Digital Signal Processing- 2019, by Jesse Engel, Lamtharn (Hanoi) Hantrakul, Chenjie Gu, Adam Roberts -
GANSynth: Adversarial Neural Audio Synthesis- 2019, by Jesse Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, & Adam Roberts -
Guitar Effects Recognition and Parameter Estimation with Convolutional Neural Networks- 2020, by Marco Comunità, Dan Stowell, Joshua D. Reiss -
Randomized Overdrive Neural Networks- 2020, by Christian J. Steinmetz, Joshua D. Reiss -
auraloss: Audio-focused loss functions in PyTorch- 2020, by Christian J. Steinmetz, Joshua D. Reiss -
A deep learning approach to sound classification for film audio post-production- 2020, by Guillermo G Peeters, Joshua D Reiss -
Modeling plate and spring reverberation using a DSP-informed deep neural network- 2020, by Marco A. Martínez Ramírez, Emmanouil Benetos, Joshua D. Reiss -
Investigation of a real-time hearing loss simulation for use in audio production- 2020, by Angeliki Mourgela, Trevor R. Agus, and Joshua D. Reiss -
Real-Time Sound Synthesis of Audience Applause- 2020, by J. R. R. Lee and J. D. Reiss -
A Comparison of Virtual Analog Modelling Techniques for Desktop and Embedded Implementations- 2020, by Jatin Chowdhury -
Efficient Neural Networks for Real-time Analog Audio Effect Modeling- 2021, by Christian J. Steinmetz, Joshua D. Reiss -
A Vacuum-Tube Guitar Amplifier Model Using Long/Short-Term Memory Networks(Sci-Hub) - 2018, by Zhichen Zhang; Edward Olbrych; Joseph Bruchalski; Thomas J. McCormick; David L. Livingston -
Real Time Emulation of Parametric Guitar Tube Amplifier With Long Short Term Memory Neural Network- 2018, by Thomas Schmitz, Jean-Jacques Embrechts -
WaveNet: A Generative Model for Raw Audio- 2016, by Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, Koray Kavukcuoglu -
Real-time Timbre Transfer and Sound Synthesis using DDSP- 2021, by Francesco Ganis, Erik Frej Knudesn, Søren V. K. Lyster, Robin Otterbein, David Südholt, Cumhur Erkut -
Steerable discovery of neural audio effects- 2021, by Christian J. Steinmetz and Joshua D. Reiss -
SignalTrain: Profiling Audio Compressors with Deep Neural Networks- 2019, by Scott H. Hawley, Benjamin Colburn, Stylianos I. Mimilakis -
Neural Parametric Equalizer Matching Using Differentiable Biquads- 2020, Shahan Nercessian, iZotope, Inc. -
Grey Box Modelling of Dynamic Range Compression- 2022, Alec Wright, Vesa Välimäki -
Automatic music mixing with deep learning and out-of-domain data- 2022, Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Giorgio Fabbro, Stefan Uhlich, Chihiro Nagashima, Yuki Mitsufuji -
Fast Temporal Convolutions for Real-Time Audio Signal Processing- 2022, Stepan Miklanek, Jiri Schimmel -
Pruning Deep Neural Network Models of Guitar Distortion Effects- 2022, David Südholt; Alec Wright; Cumhur Erkut; Vesa Välimäki
