Abstract
This paper introduces ALYSIA: Automated LYrical SongwrIting Application. ALYSIA is based on a machine learning model using Random Forests, and we discuss its success at pitch and rhythm prediction. Next, we show how ALYSIA was used to create original pop songs that were subsequently recorded and produced. Finally, we discuss our vision for the future of Automated Songwriting for both co-creative and autonomous systems.
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Notes
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- 4.
Brown corpus: http://www.hit.uib.no/icame/brown/bcm.html.
- 5.
CMUDict v0.07, Carnegie Mellon University.
- 6.
Due to the difficulties in attaining MXL files, we are currently creating a new larger corpus of songs, which will be analyzed in future work.
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Ackerman, M., Loker, D. (2017). Algorithmic Songwriting with ALYSIA. In: Correia, J., Ciesielski, V., Liapis, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Lecture Notes in Computer Science(), vol 10198. Springer, Cham. https://doi.org/10.1007/978-3-319-55750-2_1
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DOI: https://doi.org/10.1007/978-3-319-55750-2_1
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