The Mensural Scoring-up Tool
Pages 9 - 19
Abstract
Vocal polyphonic music from 1280 to 1600 is written in mensural notation and it is typically presented in a layout with separate parts. In this paper, we introduce the Mensural Scoring-up Tool, a set of scripts designed to automatically transform the separate-parts representation of the music into a score by dealing with the context-dependent nature of the notation through the implementation of the principles of imperfection and alteration, outlined by Franco of Cologne (ca. 1280). This tool exhibits 97% accuracy in a corpus of fourteenth- and fifteenth-century pieces, including both black and white mensural notation. The new encoding generated by the Scoring-up Tool could be useful for digital libraries that have digitized their collections of mensural music documents since the symbolic score could accompany the digital images providing a representation that makes the music accessible to a larger audience—since these symbolic scores can easily allow for a conversion into modern values and for playback—and that facilitates music analysis for the experts.
References
[1]
Willi Apel. 1953. The Notation of Polyphonic Music 900–1600(fifth ed.). The Medieval Academy of America, Cambridge, MA.
[2]
Jorge Calvo-Zaragoza and David Rizo. 2018. End-to-end neural optical music recognition of monophonic scores. Applied Sciences 8(2018), 606–23.
[3]
Jorge Calvo-Zaragoza, David Rizo, and José Manuel Iñesta. 2016. Two (note) heads are better than one: Pen-based multimodal interaction with music scores. In Proceedings of the 17th International Society for Music Information Retrieval Conference. New York, NY, 509–14.
[4]
Christophe Dalitz and Thomas Karsten. 2005. Using the Gamera framework for building a lute tablature recognition system. In Proceedings of the 6th International Conference on Music Information Retrieval. London, UK, 478–81.
[5]
Karen Desmond. 2018. Measuring Polyphony: Digital Encodings of Late Medieval Music. Retrieved March 14, 2019 from https://measuringpolyphony.org
[6]
Karen Desmond and Martha E. Thomae. 2017. A methodology for encoding mensural music: Introducing the Mensural MEI Translator. (2017). Music Encoding Conference, Tours, France.
[7]
Michael Droettboom, Ichiro Fujinaga, Karl MacMillan, G. Sayeed Choudhury, Tim DiLauro, Mark Patton, and Teal Anderson. 2002. Using the Gamera framework for the recognition of cultural heritage materials. In Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries. Portland, OR, 11–7.
[8]
Ross W. Duffin. 1983. Guillaume Dufay Chansons, forty-five settings in original notation: from Oxford, Bodleian Library, MS Canonici 213. Ogni Sorte Editions, Miami, FL.
[9]
Andrew Hankinson, Perry Roland, and Ichiro Fujinaga. 2011. The Music Encoding Initiative as a document-encoding framework. In Proceedings of the 12th International Society for Music Information Retrieval Conference. Miami, FL, 293–8.
[10]
Karl MacMillan, Michael Droettboom, and Ichiro Fujinaga. 2001. Gamera: A Python-based toolkit for structured document recognition. In Tenth International Python Conference.
[11]
Alexander Pacha and Jorge Calvo-Zaragoza. 2018. Optical music recognition in mensural notation with region-based convolutional neural networks. In Proceedings of the 19th International Society for Music Information Retrieval Conference. Paris, France, 23–7.
[12]
Carl Parrish. 1978. The Notation of Medieval Music. Pendragon Press, New York, NY.
[13]
Laurent Pugin. 2006. Optical music recognition of early typographic prints using Hidden Markov Models. In Proceedings of the 7th International Conference on Music Information Retrieval. Victoria, BC Canada, 53–6.
[14]
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, 107–12.
[15]
David Rizo, Nieves Pascual León, and Craig Stuart Sapp. 2018. White mensural manual encoding: From Humdrum to MEI. Cuadernos de Investigación Musical6 (2018), 373–93.
[16]
Perry Roland. 2002. The Music Encoding Initiative (MEI). In Proceedings of the First International Conference on Musical Application Using XML. Glasgow, Scotland, UK, 55–9.
[17]
Perry Roland, Andrew Hankinson, and Laurent Pugin. 2014. Early music and the Music Encoding Initiative. Early Music 42, 4 (2014), 605–11.
[18]
W. Oliver Strunk and Leo Treitler. 1998. Musical theory in the middle ages. In Antiquity and the Middle Ages. Source readings in music history, Vol. 2. Norton, New York, Chapter IV, 227–45.
[19]
Martha E. Thomae. 2017. Automatic Scoring up of Mensural Music using Perfect Mensurations, 1300–1550. Master’s thesis. McGill University, Montréal, Canada.
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Published: 09 November 2019
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DLfM '19: 6th International Conference on Digital Libraries for Musicology
November 9, 2019
The Hague, Netherlands
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