Exploring Graph Representation of Chorales

• URL: http://arxiv.org/abs/2201.11745v1
• Date: Thu, 27 Jan 2022 09:46:10 GMT
• Title: Exploring Graph Representation of Chorales
• Authors: Somnuk Phon-Amnuaisuk
• Abstract summary: This work explores overlapping areas music, graph theory, and machine learning. An embedding representation of a node, in a weighted undirected graph $mathcalG$, is a representation that captures the meaning of nodes in an embedding space.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work explores areas overlapping music, graph theory, and machine learning. An embedding representation of a node, in a weighted undirected graph $\mathcal{G}$, is a representation that captures the meaning of nodes in an embedding space. In this work, 383 Bach chorales were compiled and represented as a graph. Two application cases were investigated in this paper (i) learning node embedding representation using \emph{Continuous Bag of Words (CBOW), skip-gram}, and \emph{node2vec} algorithms, and (ii) learning node labels from neighboring nodes based on a collective classification approach. The results of this exploratory study ascertains many salient features of the graph-based representation approach applicable to music applications.

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