Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks

• URL: http://arxiv.org/abs/2002.10266v1
• Date: Fri, 21 Feb 2020 09:36:24 GMT
• Title: Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks
• Authors: Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt
• Abstract summary: We propose a two-stage LSTM-based model for lead sheet generation, in which the harmonic and rhythmic templates of the song are produced first, after which, in a second stage, a sequence of melody notes is generated conditioned on these templates. A subjective listening test shows that our approach outperforms the baselines and increases perceived musical coherence.
• Score: 5.57310999362848
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Music that is generated by recurrent neural networks often lacks a sense of direction and coherence. We therefore propose a two-stage LSTM-based model for lead sheet generation, in which the harmonic and rhythmic templates of the song are produced first, after which, in a second stage, a sequence of melody notes is generated conditioned on these templates. A subjective listening test shows that our approach outperforms the baselines and increases perceived musical coherence.

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