Drafting the Landscape of Computational Musicology Tools: a Survey-Based Approach
Year: 2025
Type: conference-paper
Study design: Observational Study
Abstract: Since the 60s, musicology has been increasingly impacted by computational tools in various ways, from systematic analysis approaches to modeling of creativity. This article presents a comprehensive assessment of the current state of Computational Musicology tools based on survey data collected from practitioners in the field. We gathered information on tool usage patterns, common analytical tasks, user satisfaction levels, data characteristics, and prioritized features across four distinct domains: symbolic music, music-related imagery, audio, and text. Our findings reveal significant gaps between current tooling capabilities and user needs, highlighting some limitations of these tools across all domains. This assessment contributes to the ongoing dialogue between tool developers and music scholars, aiming to enhance the effectiveness and accessibility of computational methods in musicological research.
Institution: Gran Sasso Science Institute
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414416202