Classification of Guitar Effects and Extraction of Their Parameter Settings from Instrument Mixes Using Convolutional Neural Networks-Reference-Cited by-同舟云学术

Classification of Guitar Effects and Extraction of Their Parameter Settings from Instrument Mixes Using Convolutional Neural Networks

Published:2022 Issue: Volume: Page:101-116
ISSN:0302-9743
Container-title:Artificial Intelligence in Music, Sound, Art and Design
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Author:

Hinrichs Reemt,Gerkens Kevin,Ostermann Jörn

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-03789-4_7

Reference10 articles.

1. Comunità, M., Stowell, D., Reiss, J.D.: Guitar effects recognition and parameter estimation with convolutional neural networks. J. Audio Eng. Soc. 69(7/8), 594–604 (2021)

2. Eichas, F., Fink, M., Zölzer, U.: Feature design for the classification of audio effect units by input/output measurements. In: Proceedings of the 18th International Conference on Digital Audio Effects (DAFx-2015) (2015)

3. Lecture Notes in Electrical Engineering;M Jeevan,2017

4. Jürgens, H., Hinrichs, R., Ostermann, J.: Recognizing guitar effects and their parameter settings. In: Proceedings of the 23rd International Conference on Digital Audio Effects (DAFx2020) (2020)

5. Müller, M.: Fundamentals of Music Processing: Using Python and Jupyter Notebooks. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-69808-9

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