On the Development and Practice of AI Technology for Contemporary Popular Music Production

Autor: Emmanuel Deruty, Maarten Grachten, Stefan Lattner, Javier Nistal, Cyran Aouameur

Publikováno v: Transactions of the International Society for Music Information Retrieval, Vol 5, Iss 1 (2022)

Although the use of AI technology for music production is still in its infancy, it has the potential to make a lasting impact on the way we produce music. In this paper we focus on the design and use of AI music tools for the production of contempora

Externí odkaz: https://doaj.org/article/a73b45c203634f5da8ad336869fcb61e

BassNet: A Variational Gated Autoencoder for Conditional Generation of Bass Guitar Tracks with Learned Interactive Control

Autor: Emmanuel Deruty, Maarten Grachten, Stefan Lattner

Publikováno v: Applied Sciences
Volume 10
Issue 18
Applied Sciences, Vol 10, Iss 6627, p 6627 (2020)

Deep learning has given AI-based methods for music creation a boost by over the past years. An important challenge in this field is to balance user control and autonomy in music generation systems. In this work, we present BassNet, a deep learning mo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25500dcbabb63a9013e86a1661cc4289

System & Contrast

Autor: Gabriel Sargent, Emmanuel Deruty, Emmanuel Vincent, Frédéric Bimbot

Publikováno v: Music Perception. 33:631-661

This article introduces a model called “System & Contrast” (S&C), which aims at describing the inner organization of structural segments within music pieces in terms of : (i) a carrier system, i.e. a sequence of morphological elements forming a m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::08ca2e8d175f9e56270cd613d1bfc977
https://doi.org/10.1525/mp.2016.33.5.631

About Dynamic Processing in Mainstream Music

Autor: Emmanuel Deruty, Damien Tardieu

Publikováno v: Journal of the Audio Engineering Society. 62:42-55

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::450e9bb9988eedf6377f6da5204e2197
https://doi.org/10.17743/jaes.2014.0001

Sound indexing using morphological description

Autor: Emmanuel Deruty, Geoffroy Peeters

Publikováno v: IEEE Transactions on Audio, Speech and Language Processing
IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2010
IEEE Transactions on Audio, Speech and Language Processing, 2010

Sound sample indexing usually deals with the recognition of the source/cause that has produced the sound. For abstract sounds, sound effects, unnatural, or synthetic sounds, this cause is usually unknown or unrecognizable. An efficient description of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb8c413cb30714dd58a3467822000f2f
https://hal.archives-ouvertes.fr/hal-01106507