Video Background Music Generation with Controllable Music Transformer
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Open Access
- 17 October 2021
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 2037-2045
Abstract
In this work, we address the task of video background music generation. Some previous works achieve effective music generation but are unable to generate melodious music specifically for a given video, and none of them considers the video-music rhythmic consistency. To generate the background music that matches the given video, we first establish the rhythmic relationships between video and background music. In particular, we connect timing, motion speed, and motion saliency from video with beat, simu-note density, and simu-note strength from music, respectively. We then propose CMT, a Controllable Music Transformer that enables the local control of the aforementioned rhythmic features, as well as the global control of the music genre and the used instrument specified by users. Objective and subjective evaluations show that the generated background music has achieved satisfactory compatibility with the input videos, and at the same time, impressive music quality.Keywords
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Funding Information
- Beijing Natural Science Foundation (4202034)
- Fundamental Research Funds for the Central Universities
- National Natural Science Foundation of China (61876177)
This publication has 4 references indexed in Scilit:
- PopMAG2020
- Pop Music Transformer2020
- Visual rhythm and beatACM Transactions on Graphics, 2018
- MuseGAN: Multi-track Sequential Generative Adversarial Networks for Symbolic Music Generation and AccompanimentProceedings of the AAAI Conference on Artificial Intelligence, 2018