Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

An investigation of music analysis by the application of grammar-based compressors

Humphreys, David, Sidorov, Kirill ORCID:, Jones, Andrew and Marshall, David 2021. An investigation of music analysis by the application of grammar-based compressors. Journal of New Music Research 50 (4) , pp. 312-341. 10.1080/09298215.2021.1978505

[thumbnail of 09298215.2021.pdf]
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (5MB) | Preview


Many studies have presented computational models of musical structure, as an important aspect of musicological analysis. However, the use of grammar-based compressors to automatically recover such information is a relatively new and promising technique. We investigate their performance extensively using a collection of nearly 8000 scores, on tasks including error detection, classification, and segmentation, and compare this with a range of more traditional compressors. Further, we detail a novel method for locating transcription errors based on grammar compression. Despite its lack of domain knowledge, we conclude that grammar-based compression offers competitive performance when solving a variety of musicological tasks.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Advanced Research Computing @ Cardiff (ARCCA)
Additional Information: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( licenses/by-nc-nd/4.0/)
Publisher: Taylor and Francis Group
ISSN: 0929-8215
Date of First Compliant Deposit: 11 October 2021
Date of Acceptance: 1 September 2021
Last Modified: 17 May 2023 21:24

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics