AUTOMATIC MELODY REDUCTION VIA SHORTEST PATH FINDING
Wang, Ziyu Wu, Yuxuan Dannenberg, Roger B. Xia, Gus
Wang, Ziyu
Wu, Yuxuan
Dannenberg, Roger B.
Xia, Gus
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Department
Machine Learning
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Melody reduction, as an abstract representation of musical compositions, serves not only as a tool for music analysis but also as an intermediate representation for structured music generation. Prior computational theories, such as the Generative Theory of Tonal Music, provide insightful interpretations of music, but they are not fully automatic and usually limited to the classical genre. In this paper, we propose a novel and conceptually simple computational method for melody reduction using a graph-based representation inspired by principles from computational music theories, where the reduction process is formulated as finding the shortest path. We evaluate our algorithm on pop, folk, and classical genres, and experimental results show that the algorithm produces melody reductions that are more faithful to the original melody and more musically coherent than other common melody downsampling methods. As a downstream task, we use melody reductions to generate symbolic music variations. Experiments show that our method achieves higher quality than state-of-the-art style transfer methods.1.
Citation
Z. Wang, Y. Wu, R. Dannenberg, and G. Xia, “Automatic Melody Reduction via Shortest Path Finding”, doi: 10.5281/ZENODO.17811381.
Source
Proceedings of the International Society for Music Information Retrieval Conference
Conference
26th International Society for Music Information Retrieval Conference (ISMIR 2025)
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Source
26th International Society for Music Information Retrieval Conference (ISMIR 2025)
Publisher
International Society for Music Information Retrieval