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Encoding music performance data in Humdrum and MEI

Abstract

This paper proposes extensions to two existing music encoding formats, Humdrum and Music Encoding Initiative (MEI), in order to facilitate linking music performance data with corresponding score information. We began by surveying music scholars about their needs for encoding timing, loudness, pitch, and timbral performance data. We used the results of this survey to design and implement new spines in Humdrum syntax to encode summary descriptors at note, beat, and measure levels and new attributes in the MEI format to encode both note-wise summaries and continuous data. These extensions allow for multiple performances of the same piece to be directly compared with one another, facilitating both humanistic and computational study of recorded musical performances.

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Notes

  1. http://mtg.upf.edu/download/datasets/eep-dataset.

  2. https://code.soundsoftware.ac.uk/projects/dai2015analysis-resources.

  3. http://www.mazurka.org.uk/.

  4. http://www.sonicvisualiser.org/.

  5. http://www.vamp-plugins.org/.

  6. http://www.ampact.org/.

  7. http://www.tei-c.org/Vault/P4/.

  8. http://www.tei-c.org/Guidelines/P5/.

  9. The MEI.performanceEXT module is available as an ODD at: https://github.com/jcdevaney/meiPerformanceExt.

  10. http://web.mit.edu/music21/.

  11. http://www.ampact.org.

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Acknowledgements

This work was supported by the National Endowment for the Humanities’ Office of Digital Humanities under Grant [number HD-228966-15] and the Fonds de recherche du Québec – Société et culture.

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Correspondence to Johanna Devaney.

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Devaney, J., Léveillé Gauvin, H. Encoding music performance data in Humdrum and MEI. Int J Digit Libr 20, 81–91 (2019). https://doi.org/10.1007/s00799-017-0229-3

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Keywords

  • Digital musicology
  • Music performance
  • Music encoding
  • Music representations