LooperGP: A Loopable Sequence Model for Live Coding Performance using GuitarPro Tablature

Created by W.Langdon from gp-bibliography.bib Revision:1.7778

@InProceedings{Adkins:2023:evomusart,

• author = "Sara Adkins and Pedro Sarmento and Mathieu Barthet",
• title = "{LooperGP}: A Loopable Sequence Model for Live Coding Performance using GuitarPro Tablature",
• booktitle = "12th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMusArt 2023",
• year = "2023",
• month = apr # " 12-14",
• editor = "Colin Johnson and Nereida Rodriguez-Fernandez and Sergio M. Rebelo",
• series = "LNCS",
• volume = "13988",
• publisher = "Springer Verlag",
• address = "Brno, Czech Republic",
• pages = "3--19",
• organisation = "EvoStar, Species",
• keywords = "genetic algorithms, genetic programming, Controllable Music Generation, Sequence Models, Live Coding, Transformers, AI Music, Loops, Guitar Tabs",
• isbn13 = "978-3-031-29956-8",
• DOI = "doi:10.1007/978-3-031-29956-8_1",
• data_url = "https://github.com/dada-bots/dadaGP",
• size = "17 pages",
• abstract = "Despite their impressive offline results, deep learning models for symbolic music generation are not widely used in live performances due to a deficit of musically meaningful control parameters and a lack of structured musical form in their outputs. To address these issues we introduce LooperGP, a method for steering a Transformer-XL model towards generating loopable musical phrases of a specified number of bars and time signature, enabling a tool for live coding performances. We show that by training LooperGP on a dataset of 93681 musical loops extracted from the DadaGP dataset [Data GuitarPro], we are able to steer its generative output towards generating three times as many loopable phrases as our baseline. In a subjective listening test conducted by 31 participants, LooperGP loops achieved positive median ratings in originality, musical coherence and loop smoothness, demonstrating its potential as a performance tool.",
• notes = "http://www.evostar.org/2023/ EvoMusArt2023 held in conjunction with EuroGP'2023, EvoCOP2023 and EvoApplications2023",

}

Genetic Programming entries for Sara Adkins Pedro Sarmento Mathieu Barthet

Citations