mchijmma / modeling-time-varying

A general-purpose deep learning approach to model time-varying audio effects - website:

Audio examples for the paper:

Martínez Ramírez M. A., Benetos, E. and Reiss J. D., “A general-purpose deep learning approach to model time-varying audio effects” in the 22nd International Conference on Digital Audio Effects (DAFx-19), Birmingham, UK, September 2019.

View the source code: CRAFx -> Models.py

chorus

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- target

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flanger

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phaser

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tremolo

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vibrato

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auto-wah

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ring-modulator

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Leslie speaker (left channel)

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Leslie speaker (right channel)

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chorus+overdrive

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flanger+overdrive

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phaser+overdrive

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tremolo+overdrive

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vibrato+overdrive

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auto-wah+overdrive

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auto-wah (envelope follower)

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compressor

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multiband compressor

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Citation

@inproceedings{martinez2019general,
title={A general-purpose deep learning approach to model time-varying audio effects},
author={Mart'{i}nez Ram'{i}rez, Marco A, and Benetos, Emmanouil and Reiss, Joshua D},
booktitle={22nd International Conference on Digital Audio Effects (DAFx-19)},
month = {September},
year = {2019},
location = {Birmingham, UK}
}