Studying Music is Difficult and Important: Challenges of Music Knowledge Representation

Author Donald Byrd

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Donald Byrd

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Donald Byrd. Studying Music is Difficult and Important: Challenges of Music Knowledge Representation. In Knowledge representation for intelligent music processing. Dagstuhl Seminar Proceedings, Volume 9051, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)


* Music is an art, so many musicians try to use its elements in interesting and original ways, not standardized and ordinary ways. (cf. Collins 2006) * Music is a performing art, so we have both performances and symbolic representations (both scores and transcriptions of performances). * Much music, especially Western, has synchronization requirements of a complexity equalled in no presentation of information for human consumption – art form or other -- we are aware of. * Music involves many different instruments, often in groups. No other art form we know of has anything like this, and it opens up the possibility of versions of a given work for other ensembles or at other levels of technical demands. * Music is often combined with text. * Music is extremely popular, so, for many works, numerous versions actually exist. For all these reasons, music is uniquely difficult, and uniquely valuable, to deal with -- especially by computer. To support the argument, we give examples in the form of conventional Western music notation that either violate – in several cases, blatantly – the supposed rules of music notation, or that bring up difficult issues of music representation (see Byrd 1994 and Byrd 2009). We also give examples in audio form from some unpublished work of ours to point out the astounding range of what is considered music by one culture or another. References Byrd, Donald (1994). Music Notation Software and Intelligence. Computer Music Journal 18(1), pp. 17-20; available (in scanned form) at . Byrd, Donald (2009). Gallery of Interesting Music Notation. Available at . Collins, Nick (2006, Winter). Composing to Subvert Content Retrieval Engines. ICMA Array, Winter 2006, pp. 37-41.
  • Music computing
  • representation


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