Music Embedding: A Tool for Incorporating Music Theory into Computational Music Applications
SeyyedPooya HekmatiAthar, Mohd Anwar

TL;DR
This paper introduces a new open-source music embedding tool that integrates music theory into computational representations, enhancing the analysis and processing of musical data.
Contribution
It presents a novel music embedding approach based on music theory, bridging the gap between theoretical concepts and computational applications.
Findings
Effective representation of classical music pieces
Improved analysis capabilities for music data
Open-source tool available for researchers
Abstract
Advancements in the digital technologies have enabled researchers to develop a variety of Computational Music applications. Such applications are required to capture, process, and generate data related to music. Therefore, it is important to digitally represent music in a music theoretic and concise manner. Existing approaches for representing music are ineffective in terms of utilizing music theory. In this paper, we address the disjoint of music theory and computational music by developing an opensource representation tool based on music theory. Through the wide range of use cases, we run an analysis on the classical music pieces to show the usefulness of the developed music embedding.
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Taxonomy
TopicsNeuroscience and Music Perception · Music and Audio Processing · Music Technology and Sound Studies
