2021/04/24 by SeyyedPooya HekmatiAthar, HekmatiAthar, SeyyedPooya, Mohd Anwar +1
Computer Science · Neuroscience · #Artificial Intelligence (cs.AI) #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Music Technology and Sound Studies #Music and Audio Processing #Neuroscience and Music Perception #Sound (cs.SD) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2104.11880
openalex publication_date 2021/04/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.