Exploring Graph Representation of Chorales
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.
- Publication:
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arXiv e-prints
- Pub Date:
- January 2022
- DOI:
- 10.48550/arXiv.2201.11745
- arXiv:
- arXiv:2201.11745
- Bibcode:
- 2022arXiv220111745P
- Keywords:
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- Computer Science - Machine Learning;
- Computer Science - Artificial Intelligence;
- Computer Science - Sound;
- Electrical Engineering and Systems Science - Audio and Speech Processing
- E-Print:
- 13 pages, 4 figures