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(Re)Shaping Musical Gesture: Modelling Voice Balance and Overall Dynamics Contour

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From Sounds to Music and Emotions (CMMR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7900))

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Abstract

This research focuses on identifying and modelling performers’ preferred strategies for achieving expressive performances. This paper reports on the results of analysis of a professional pianist’s practice session of Chopin’s 2nd Ballade, Op. 38. The analysis focused on his approach to balance voices within polyphonic texture. The model for balance of voices is a weighted average of several renditions of the excerpt. Differences of average balance of voices are statistically significant, which suggests that each voice varies around a preferred, overall balance. Tukey HSD reveals that each of the four voices of the excerpt (beginning of the musical work) had been performed within an independent dynamic range. New models representing similar renditions were created using clustering techniques. Those models can then be transformed into new, reshaped performances.

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References

  1. Gualda, F.: Subtleties of Inflection and Musical Noesis: Computational and Cognitive Approaches to Aural Assessment of Music Performance. PhD. diss. Queen’s University Belfast, Belfast (2011)

    Google Scholar 

  2. Nattiez, J.J.: Music and Discourse: Toward a Semiology of Music. Princeton University Press, Princeton (1990); Abbate, C. (Trans.)

    Google Scholar 

  3. Palmer, C.: Anatomy of a Performance: Sources of Musical Expression. Music Perception 13(3), 433–453 (1996)

    Article  MathSciNet  Google Scholar 

  4. Hatten, R.: Interpreting Musical Gestures, Topics, and Tropes. Indiana University Press, Bloomington (2004)

    Google Scholar 

  5. Goebl, W.: Melody lead in piano performance: Expressive device or artifact? Journal of the Acoustical Society of America 110(1), 563–752 (2001)

    Article  Google Scholar 

  6. Widmer, G., Goebl, W.: Computational Models of Expressive Music Performance: The State of the Art. Journal of New Music Research 33(3), 203–216 (2004)

    Article  Google Scholar 

  7. Gingrass, B.: Expressive Strategies and Performer-Listener Communication in Organ Performance. PhD. diss. McGill University, Montreal (2008)

    Google Scholar 

  8. Carvalho, A.R., Barros, L.C.: Using the organ as a practice strategy while learning a fugue on the piano: An experimental study focusing on polyphonic listening. In: Performa 2009 Conference on Performance Studies (2009)

    Google Scholar 

  9. Clarke, E.: Ways of Listening. Oxford University Press, Oxford (2004)

    Google Scholar 

  10. Ericsson, K.A.: The Influence of Experience and Deliberate Practice on the Development of Superior Expert Performance. In: Ericsson, K.A., Charness, N., Feltovich, P., Hoffman, R.R. (eds.) Cambridge Handbook of Expertise and Expert Performance, pp. 685–706. Cambridge University Press, Cambridge (2006)

    Chapter  Google Scholar 

  11. Murtagh, F., Legendre, P.: Ward’s Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm. arXiv:1111.6285 (p.2) Cornell University Library (2011)

    Google Scholar 

  12. Ward Jr., J.H.: Hierarchical Grouping to Optimize an Objective Function. Journal of the American Statistical Association 48, 236–244 (1963)

    Article  Google Scholar 

  13. Winold, A.: Music Analysis: Purposes, Paradigms, and Problems. Journal of Music Theory Pedagogy 7, 29–40 (1993)

    Google Scholar 

  14. Chopin, F.: 2ème ballade. Beitkopf&Härtel, Leipzig (1840)

    Google Scholar 

  15. Chopin, F.: Dzielawszystkie Fryderyka Chopina. In: Paderewsky, I.J., Bronarski, L., Turczynski, J. (eds.) Ballades, vol. III. Institut Pryderyka Chopina, Warsaw (1949)

    Google Scholar 

  16. Chopin, F.: Oeuvres complètes de Frédéric Chopin. Bote&Bock, Berlin (1880); Klindworth, K. (ed.)

    Google Scholar 

  17. Bregman, A.S.: Auditory Scene Analysis: The Perceptual Organization of Sound. MIT Press, Cambridge (1990)

    Google Scholar 

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Yamaguchi, R., Gualda, F. (2013). (Re)Shaping Musical Gesture: Modelling Voice Balance and Overall Dynamics Contour. In: Aramaki, M., Barthet, M., Kronland-Martinet, R., Ystad, S. (eds) From Sounds to Music and Emotions. CMMR 2012. Lecture Notes in Computer Science, vol 7900. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41248-6_26

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  • DOI: https://doi.org/10.1007/978-3-642-41248-6_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41247-9

  • Online ISBN: 978-3-642-41248-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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