MINGUS: Melodic improvisation neural generator using Seq2Seq

Madaghiele, Vincenzo; Lisena, Pasquale; Troncy, Raphaël
ISMIR 2021, 22nd International Society for Music Information Retrieval Conference, 8-12 November 2021, Online Event

Sequence to Sequence (Seq2Seq) approaches have shown good performances in automatic music generation. We introduce MINGUS, a Transformer-based Seq2Seq architecture for modelling and generating monophonic jazz melodic lines. MINGUS relies on two dedicated embedding models (respectively for pitch and duration) and exploits
in prediction features such as chords (current and following), bass line, position inside the measure. The obtained results are comparable with the state of the art of music generation with neural models, with particularly good performances on jazz music.

Type:
Conférence
Date:
2021-11-07
Department:
Data Science
Eurecom Ref:
6622
Copyright:
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PERMALINK : https://www.eurecom.fr/publication/6622