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Gran Cassa and the Adaptive Instrument Feed-Drum

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Computer Music Modeling and Retrieval (CMMR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3902))

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Abstract

The physical-mathematical models of orchestral instruments represent an important theoretical and experimental support for the composer and for the application of new acoustic and performance criteria. Western music has linked its evolution to the transformation of instruments and performance techniques through the constant interaction between the expressive demands of the musical language (e.g. pitch range and control), acoustic requirements (e.g. sound irradiation level and type), sound emission techniques (e.g. ergonomics and excitation control). There is a constant interaction and reciprocal adaptation between the construction of the instrument and the composition and performance of music. For instance, consider how the tenth-century Viella evolved into the family of Renaissance Violas and then into the family of Violins. In terms of composition this coincides with the transition from monodic forms that duplicate voice and syllabic rhythm to the formal autonomy of instrumental music, with the spread of the frequency range, to the grand forms and orchestral ensembles of Baroque music. Executive technique is integrated in this process, since the player not only fills the role of agent producing the acoustic rendering, but also of expert demonstrating the criteria of agility and ergonomics of the instrument and inventing solutions of adaptation and virtuosity.

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References

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© 2006 Springer-Verlag Berlin Heidelberg

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Lupone, M., Seno, L. (2006). Gran Cassa and the Adaptive Instrument Feed-Drum. In: Kronland-Martinet, R., Voinier, T., Ystad, S. (eds) Computer Music Modeling and Retrieval. CMMR 2005. Lecture Notes in Computer Science, vol 3902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751069_14

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  • DOI: https://doi.org/10.1007/11751069_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34027-0

  • Online ISBN: 978-3-540-34028-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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