ABSTRACT
In this paper, we discuss how different encodings in symbolic music files can have consequences for music analysis, where a truthful representation, not only of the musical score, but of the semantics of the music, can change the results of music analysis tools. We introduce a series of examples in which different encodings effectively modify the content of two---apparently equivalent---symbolic music files. These examples have been obtained from comparing three different encodings of a string quartet movement by Ludwig van Beethoven.
We present two scenarios in which encoding discrepancies may be introduced. In the first scenario, they have been introduced during the encoding of the symbolic music file by either the music notation software or the human encoder. The discrepancies introduced in this scenario are typically difficult to notice because they are visually identical to an accurate encoding. In the second scenario, the discrepancies have been introduced during the translation of the original file into other symbolic formats. In this scenario, the discrepancies may be related to propagating errors in the original encoding or to an erroneous translation of certain attributes of the musical content. Finally, we discuss the possibility of using the examples provided here for the mitigation of some of these discrepancies in the future.
- Christopher Antila and Julie Cumming. 2014. The VIS Framework: Analyzing counterpoint in large datasets. In Proceedings of the 15th International Society for Music Information Retrieval Conference. Taipei, Taiwan, 71--76.Google Scholar
- Michael Scott Cuthbert and Christopher Ariza. 2010. music21: A toolkit for computer-aided musicology and symbolic music data. In Proceedings of the 11th International Society for Music Information Retrieval Conference. Utrecht, Netherlands, 637--642.Google Scholar
- Audrey Laplante and Ichiro Fujinaga. 2016. Digitizing musical scores: Challenges and opportunities for libraries. In Proceedings of the 3rd International Workshop on Digital Libraries for Musicology. New York, NY, 45--48. Google ScholarDigital Library
- Cory McKay and Julie Cumming. 2018. Methodologies for creating symbolic early music corpora for musicological research. In Proceedings of the 19th International Society for Music Information Retrieval Conference. Paris, France.Google Scholar
- Laurent Pugin. 2015. The challenge of data in digital musicology. Frontiers in Digital Humanities 2 (2015), 4.Google ScholarCross Ref
- Laurent Pugin, Rodolfo Zitellini, and Perry Roland. 2014. Verovio: A library for engraving MEI music notation into SVG. In Proceedings of the 15th International Society for Music Information Retrieval Conference. Taipei, Taiwan, 107--112.Google Scholar
Index Terms
- Encoding matters
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