Reviews: Hidden Structure: Music Analysis Using Computers and Music21: A Toolkit for Computer-Aided Musicology

Abstract

Other| April 01 2014 Reviews: Hidden Structure: Music Analysis Using Computers and Music21: A Toolkit for Computer-Aided Musicology Hidden Structure: Music Analysis Using Computers, by David Cope. Computer Music and Digital Audio Series 23. Middleton, WI: A-R Editions, 2008. xxix, 344 pp. + 1 CD-ROM.Music21: A Toolkit for Computer-Aided Musicology, by Michael Cuthbert. Version 1.5, last modified May 11, 2013. http://web.mit.edu/music21/. Ian Quinn Ian Quinn Ian Quinn is Professor of Music at Yale University, where he teaches music theory, music cognition, and computational methods in music research. Search for other works by this author on: This Site PubMed Google Scholar Journal of the American Musicological Society (2014) 67 (1): 295–307. https://doi.org/10.1525/jams.2014.67.1.295 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Ian Quinn; Reviews: Hidden Structure: Music Analysis Using Computers and Music21: A Toolkit for Computer-Aided Musicology. Journal of the American Musicological Society 1 April 2014; 67 (1): 295–307. doi: https://doi.org/10.1525/jams.2014.67.1.295 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentJournal of the American Musicological Society Search The Age of Big Data is here, and we in music studies find ourselves, as usual, both ahead of the curve and behind it. Like our cognate cousins in art history, film studies, and performance studies, we have reasonable excuse for lagging behind computational literati like Franco Moretti and Matthew Jockers, whose Stanford Literary Lab has been opening debates across the humanities1 and making headlines in the popular press. The excuse is technical: it is easy to transform literary texts into searchable data, and hard to do so for music. Insofar as the content of a novel is made out of words, it can be encoded as a long string of small numbers (representing letters and spaces) without losing any information. Even if we allow ourselves to believe that a musical score is an adequate representation of the content of a work, the encoding problem is vastly more complex.... You do not currently have access to this content.