Convolutional neural networks for the classification of guitar effects and extraction of the parameter settings of single and multi-guitar effects from instrument mixes

Autor: Reemt Hinrichs, Kevin Gerkens, Alexander Lange, Jörn Ostermann

Publikováno v: EURASIP Journal on Audio, Speech, and Music Processing, Vol 2022, Iss 1, Pp 1-21 (2022)

Abstract Guitar effects are commonly used in popular music to shape the guitar sound to fit specific genres, or to create more variety within musical compositions. The sound not only is determined by the choice of the guitar effect, but also heavily

Externí odkaz: https://doaj.org/article/aa41cd04717743b5b0c1fc3b97a16ad9

Blind extraction of guitar effects through blind system inversion and neural guitar effect modeling

Autor: Reemt Hinrichs, Kevin Gerkens, Alexander Lange, Jörn Ostermann

Publikováno v: EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-17 (2024)

Abstract Audio effects are an ubiquitous tool in music production due to the interesting ways in which they can shape the sound of music. Guitar effects, the subset of all audio effects focusing on guitar signals, are commonly used in popular music t

Externí odkaz: https://doaj.org/article/822f9e734b8c4880b171592cbb8b69f4

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Automatic Recognition of Cascaded Guitar Effects

Autor: Guo, Jinyue, McFee, Brian

Publikováno v: Guo, Jinyue McFee, Brian . Automatic Recognition of Cascaded Guitar Effects. Proceedings of the International Conference on Digital Audio Effects. 2023
Proceedings of the International Conference on Digital Audio Effects

Externí odkaz: http://hdl.handle.net/10852/105917