Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Nottingham dataset"'
Autor:
Nogales Pérez, David
L'objectiu principal d'aquest projecte és utilitzar tècniques d'aprenentatge profund per desenvolupar una eina capaç de generar exercicis de dictat melòdic significatius perquè els professors de música i els seus estudiants els utilitzin i prac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::290240beb03ab8782f7286e8a7824e0d
https://hdl.handle.net/2117/389818
https://hdl.handle.net/2117/389818
Publikováno v:
Neural Computing & Applications. Dec2021, Vol. 33 Issue 23, p16213-16228. 16p.
This paper explores the idea of utilising Long Short-Term Memory neural networks (LSTMNN) for the generation of musical sequences in ABC notation. The proposed approach takes ABC notations from the Nottingham dataset and encodes it to be fed as input
Externí odkaz:
http://arxiv.org/abs/2105.09046
This paper proposes a word representation strategy for rhythm patterns. Using 1034 pieces of Nottingham Dataset, a rhythm word dictionary whose size is 450 (without control tokens) is generated. BERT model is created to explore syntactic potentials o
Externí odkaz:
http://arxiv.org/abs/2007.10610
Most existing neural network models for music generation explore how to generate music bars, then directly splice the music bars into a song. However, these methods do not explore the relationship between the bars, and the connected song as a whole h
Externí odkaz:
http://arxiv.org/abs/1907.01607
Publikováno v:
Journal of Computer Engineering & Applications; 5/1/2023, Vol. 59 Issue 9, p27-45, 19p
Autor:
Pasa, Luca, Sperduti, Alessandro
Publikováno v:
Artificial Neural Networks in Pattern Recognition (9783319461816); 2016, p3-17, 15p
Autor:
Drott, Eric1 (AUTHOR)
Publikováno v:
Creative Industries Journal. Jul2021, Vol. 14 Issue 2, p190-207. 18p.
Publikováno v:
International Society for Music Information Retrieval Conference Proceedings; 2022, p248-255, 8p
Publikováno v:
International Society for Music Information Retrieval Conference Proceedings; 2022, p93-99, 7p