A statistical analysis of the ABC music notation corpus: exploring duplication
Walshaw, Chris ORCID: 0000-0003-0253-7779 (2014) A statistical analysis of the ABC music notation corpus: exploring duplication. In: Proceedings of the Fourth International Workshop on Folk Music Analysis (FMA2014). Computer Engineering Department, Boğaziçi University, Turkey, Istanbul, Turkey, pp. 2-9.
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Abstract
This paper presents a statistical analysis of the abc music notation corpus. The corpus contains around 435,000 transcriptions of which just over 400,000 are folk and traditional music. There is significant duplication within the corpus and so a large part of the paper discusses methods to assess the level of duplication and the analysis then indicates a headline figure of over 165,000 distinct folk and traditional melodies. The paper also describes TuneGraph, an online, interactive user interface for exploring tune variants, based on visualising the proximity graph of the underlying melodies.
Item Type: | Conference Proceedings |
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Title of Proceedings: | Proceedings of the Fourth International Workshop on Folk Music Analysis (FMA2014) |
Additional Information: | [1] This paper was first presented at the Fourth International Workshop on Folk Music Analysis (FMA2014) held from 12-13 June 2014 in Istanbul, Turkey. It was given within Session 4. Oral session: Transcription on 13 June 2014. [2] The workshop is supported by the European Research Council, Compmusic Project. [3] Published as: Walshaw, Chris (2014) A statistical analysis of the ABC music notation corpus: exploring duplication. In: Proceedings of the Fourth International Workshop on Folk Music Analysis (FMA2014). Computer Engineering Department, Boğaziçi University, Turkey, Istanbul, Turkey, pp. 2-9. |
Uncontrolled Keywords: | cultural informatics, music information retrieval, digital archives, abc music |
Subjects: | G Geography. Anthropology. Recreation > GR Folklore M Music and Books on Music > M Music Q Science > QA Mathematics |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) |
Related URLs: | |
Last Modified: | 26 Nov 2020 22:35 |
URI: | http://gala.gre.ac.uk/id/eprint/12272 |
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