Exploring annotations for musical pattern discovery gathered with digital annotation tools

Tomašević, Darian (author), Wells, Stephan (author), Yuping Ren, Iris (author), Volk, Anja (author), Pesek, Matevž (author)

The study of inter-annotator agreement in musical pattern annotations has gained increased attention over the past few years. While expert annotations are often taken as the reference for evaluating pattern discovery algorithms, relying on just one reference is not usually sufficient to capture the complex musical relations between patterns. In this paper, we address the potential of digital annotation tools to enable large-scale annotations of musical patterns, by comparing datasets gathered with two recently developed digital tools. We investigate the influence of the tools and different annotator backgrounds on the annotation process by performing inter-annotator agreement analysis and feature-based analysis on the annotated patterns. We discuss implications for further adaptation of annotation tools, and the potential for deriving reference data from such rich annotation datasets for the evaluation of automatic pattern discovery algorithms in the future.

• Language: English
• Keywords: musical pattern, digital annotation tool, inter-annotator agreement, feature analysis
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: FRI - Faculty of Computer and Information Science
• Publication status: Published
• Publication version: Version of Record
• Year: 2021
• Number of pages: Str. 194-207
• Numbering: Vol. 15, no. 2
• PID: 20.500.12556/RUL-141157
• UDC: 004:78
• ISSN on article: 1745-9745
• DOI: 10.1080/17459737.2021.1943026
• COBISS.SI-ID: 71378691
• Publication date in RUL: 23.09.2022

Record is a part of a journal

• Title: Journal of mathematics and music
• Publisher: Taylor & Francis
• ISSN: 1745-9745
• COBISS.SI-ID: 522161433

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

• Language: Slovenian
• Keywords: glasbeni vzorec, digitalna orodja za anotacijo, strinjanje anotatorjev, analiza značilk