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Proposal of an Annotation Method for Integrating Musical Technique Knowledge Using a GTTM Time-Span Tree

  • Nami IinoEmail author
  • Mayumi Shimada
  • Takuichi Nishimura
  • Hideaki Takeda
  • Masatoshi Hamanaka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11295)

Abstract

This paper proposes an annotation method for integrating the knowledge of musical techniques and musical structures. We have attempted to support musical instrument performances from the viewpoint of knowledge engineering. We focused on classical guitar, which requires many techniques, and developed guitar rendition ontology that can serve as a guideline for classical guitar performances at teaching and learning sites. In order to effectively use ontology knowledge at the sites, we need to connect it with musical structures so that the ontology data can be integrated with musical score information. Therefore, we propose a method that annotates the knowledge related to musical techniques to time-span trees obtained from time-span analysis based on the generative theory of tonal music (GTTM). We experimented with several bars of four guitar pieces and investigated how much the knowledge, which is executed with more than two notes, can add to time-span trees. Our results showed that about 76% of the ontology knowledge corresponded with the structure of time-span trees.

Keywords

Guitar rendition ontology Musical technique GTTM Time-span tree 

Notes

Acknowledgements

This work was supported by JSPS KAKENHI, Grant Numbers 17H01847 and 16H01744.

References

  1. 1.
    Zatorre, R.J., McGill, J.: Music, the food of neuroscience? Nature 434(7031), 312–315 (2005)CrossRefGoogle Scholar
  2. 2.
    Schlaug, G., Norton, A., Overy, K., Winner, E.: Effects of music training on the child’s brain and cognitive development. Ann. N. Y. Acad. Sci. 1060, 219–230 (2005)CrossRefGoogle Scholar
  3. 3.
    Nishimura, S., et al.: Employee driven approach to “knowledge explication” in elderly care service. Trans. Jpn. Soc. Artif. Intell. 32(4), C-G95_1-15 (2017)CrossRefGoogle Scholar
  4. 4.
    Iino, N., Nishimura, S., Fukuda, K., Watanabe, K., Jokinen, K., Nishimura, T.: De-velopment and use of an activity model based on structured knowledge – a music teaching support system. In: IEEE International Conference on Data Mining Workshop, pp. 576–581 (2017)Google Scholar
  5. 5.
    Iino, N., Nishimura, S., Nishimura, T., Fukuda. K., Takeda, H.: A Development of Guitar Rendition Ontology for Knowledge Sharing. SIG-SWO-044-09 (2018)Google Scholar
  6. 6.
    Cooper, G., Meyer, L.B.: The Rhythmic Structure of Music. The University of Chicago Press, Chicago (1960)Google Scholar
  7. 7.
    Narmour, E.: The Analysis and Cognition of Basic Melodic Structure. The University of Chicago Press, Chicago (1990)Google Scholar
  8. 8.
    Tempeley, D.: The Cognition of Basic Musical Structures. The MIT Press, Cambridge (2001)Google Scholar
  9. 9.
    Lerdahl, F., Jackendoff, R.: A Generative Theory of Tonal Music. The MIT Press, Cambridge (1983)Google Scholar
  10. 10.
    Hamanaka, M., Hirata, K., Tojo, S.: Implementing “a generative theory of tonal music”. J. New Music Res. 35(4), 249–277 (2006)CrossRefGoogle Scholar
  11. 11.
    Gendai Guitar Co. Ltd.: All About the Guitar Renditions. Gendai guitar, No. 595 (2013)Google Scholar
  12. 12.
    Nagashima, Y., Hashimoto, S., Hiraga, Y., Hirata, K.: Computer and music. Kyoritsu Shuppan Co., Ltd. (1999)Google Scholar
  13. 13.
    Hamanaka, M., Hirata, K., Tojo, S.: Time-span tree analyzer for polyphonic music. In: Proceedings of the 10th International Symposium on Computer Music Multidisciplinary Research, pp. 886–893 (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.RIKEN (Institute of Physical and Chemical Research)SaitamaJapan
  2. 2.National Institute of Advanced Industrial Science and TechnologyIbarakiJapan
  3. 3.SOKENDAI (Graduate University for Advanced Studies)KanagawaJapan
  4. 4.National Institute of InformaticsTokyoJapan

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