Algorithmic Songwriting with ALYSIA

TL;DR

This paper presents ALYSIA, a machine learning system for automated songwriting that predicts pitch and rhythm, enabling the creation of original pop songs and exploring future co-creative and autonomous songwriting systems.

Contribution

It introduces ALYSIA, a novel machine learning-based songwriting tool using Random Forests for pitch and rhythm prediction, and demonstrates its application in generating original songs.

Findings

ALYSIA effectively predicts pitch and rhythm for songwriting.

Original pop songs created using ALYSIA were successfully recorded.

The paper discusses future directions for automated and co-creative songwriting systems.

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.