Proceedings of the Audio Mostly 2018 on Sound in Immersion and Emotion 2018
DOI: 10.1145/3243274.3243301
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Symbolic Music Similarity through a Graph-Based Representation

Abstract: In this work, a novel representation system for symbolic music is described. The proposed representation system is graph-based and could theoretically represent music both from a horizontal (contrapuntal) and from a vertical (harmonic) point of view, by keeping into account contextual and harmonic information. It could also include relationships between internal variations of motifs and themes. This is achieved by gradually simplifying the melodies and generating layers of reductions that include only the most… Show more

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Cited by 24 publications
(15 citation statements)
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“…It would be useful to assess if using user-selected melodic seeds can make the experience more enjoyable to users. The chosen melodies should also be able to adapt to the changes in the input, possibly defining more hierarchical levels of different note densities [44] and embedding expressive performance generation to leverage such hierarchical descriptions [13,18].…”
Section: Discussionmentioning
confidence: 99%
“…It would be useful to assess if using user-selected melodic seeds can make the experience more enjoyable to users. The chosen melodies should also be able to adapt to the changes in the input, possibly defining more hierarchical levels of different note densities [44] and embedding expressive performance generation to leverage such hierarchical descriptions [13,18].…”
Section: Discussionmentioning
confidence: 99%
“…This draws heavily from [25][26][27], which introduced into the music information retrieval literature some ideas and tools from the fields of databases systems and computer linguistics (e.g., hierarchical decomposition of musical content and context-free grammars). Recently, the authors of [28] used a similar graph-based representation to study music similarity.…”
Section: Related Workmentioning
confidence: 99%
“…Each of these steps follows a different algorithm, but some information is passed on through each step. In particular, all of the steps use information about the importance of each of the generated notes, dividing them with a Schenkerian approach (Simonetta et al, 2018 ). The authors argue that this idea can be further extended to other tasks (such as form generation and harmony), including both deep learning and classical AI algorithms, trying to find the optimal combination for each task (Carnovalini, 2019 ).…”
Section: Open Challenges For Music Generation Systemsmentioning
confidence: 99%