CORDIS Project
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This project focuses on improving music generation systems by integrating structural templates and machine learning techniques. The goal is to create a framework that generates coherent and structured music compositions, enhancing applications in digital media, gaming, and interactive arts.
State-of-the-art music generation systems (Continuator, OMax, Mimi) produce music that sounds good on a note-to-note level but lacks critical structure/direction necessary for long term coherence.
To tackle this problem, we propose to generate compositions based on structural templates at varying hierarchical levels.
Our novel approach deploys machine-learning methods in an optimization context to morph existing pieces into new ones and to fuse different styles.We aim to develop a framework that…
QUEEN MARY UNIVERSITY OF LONDON
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