Humphreys, David, Sidorov, Kirill ![]() ![]() |
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Abstract
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 |
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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 (http://creativecommons.org/ 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 |
URI: | https://orca.cardiff.ac.uk/id/eprint/144808 |
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