A Personal Bibliography of Music Informatics, IR, and Visualization

Donald Byrd, Indiana University

lightly rev. late June 2013

 

"Of course I draw poorly. I like to draw poorly."     --Alleged comment by Marc Chagall, responding to criticism of his drawing by an art critic

 

I used to say this was "the most up-to-date, general bibliography of music-IR and music-informatics literature I’m aware of." I suppose that's still literally true, but it's not terribly up-to-date: it starts to fade out around 2007, and it includes very little published after 2009. Too bad, but I've simply had less and less time to devote to it. In addition, it truly is a personal bibliography, heavily biased towards my own interests. A more complete and less biased music-IR "research bibliography" appears at http://www.music-ir.org/research_home.html, but, as of the last time I checked, it was nowhere near up-to-date: it appeared to include nothing after 2003. A complete list of all ISMIR papers to date is available at http://www.ismir.net/all-papers.html; that list is exceptionally useful because it includes links to complete copies of most of the papers. Finally, Elias Pampalk maintains a list of PhD Theses and Doctoral Dissertations Related to Music Information Retrieval (and the current bibliography include very few of these).

This bibliography includes nearly all references in papers of mine published since 2001, plus all papers I’m particularly interested in from most ISMIRs and many from other sources.

It uses the American Psychological Association (APA) style with a few minor changes: page numbers are preceded by "pp." for clarity; author's names (with some exceptions, which I'm getting rid of as time allows) are given in full, since it can be very difficult to find them if for any reason you need them; etc. Note: "KW" below = "KeyWords".

 

Section A. Music IR, Digital Music Libraries and Related (music representation, music psychology, etc.)

  1. Aloupis, Greg; Fevens, Thomas; Langerman, Stefan; Matsui, Tomomi; Mesa, Antonio; Nuñez, Yurai; Rappaport, David; & Toussaint, Godfried (2006 Fall). Algorithms for Computing Geometric Measures of Melodic Similarity. Computer Music Journal 30(3), pp. 67–76.

  2. Anderies, John (2005). The Promise of Online Music. Library Journal, 1 June 2005.

  3. Assar, Vijith (2006, October). All Is Not Lost. Electronic Musician 18(5), pp. 39–47. KW: compression, lossy, perceptual transparency, metadata, ID3, MP3, WMA, AAC, Ogg Vorbis, LAME.

  4. Babbitt, Milton (1965, Spring-Summer). The Use of Computers in Musicological Research. Perspectives of New Music 3(2). KW: representation, graphemic, acoustic, auditory, combinatorial, information retrieval

  5. Baggi, Denis, & Haus, Goffredo (2009, February). The New Standard IEEE 1599, Introduction and Examples. Journal of Multimedia 4 no. 1.

  6. Bainbridge, David (1998). MELDEX: A Web-based Melodic Index Service. In Hewlett & Selfridge-Field (1998). KW: music IR, WWW, database, folksong, digital library

  7. Bainbridge, David, Cunningham, Sally Jo, & Downie, J. Stephen (2004). GREENSTONE as a Music Digital Library Toolkit. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 42–43.

  8. Bainbridge, David; Dewsnip, Michael; & Witten, Ian (2005, January). Searching Digital Music Libraries. Information Processing and Management 41(1), pp. 41–56.

  9. Bainbridge, David; Nevill-Manning, Craig; Witten, Ian; Smith, Lloyd; & McNab, Roger. (1999). Towards a Digital Library of Popular Music. In Proceedings of Digital Libraries ’99 Conference. New York: Association for Computing Machinery. KW: music IR, popular music, database, digital library

  10. Bamberger, Jeanne (2004). The development of intuitive musical understanding: a natural experiment. Psychology of Music 30(1), pp. 7–36.

  11. Barlow, Harold & Morgenstern, Sam (1948). A Dictionary of Musical Themes. New York: Crown Publishers. From the Preface: "This work contains about 10,000 themes. They have been chosen primarily from recorded, instrumental pieces... We feel that the book contains almost all of the themes the average and even the more erudite listener might want to look up." Contains a lengthy index (by pitch class only, all themes transposed to C) as well as conventional music notation for the themes. The book has had much influence on music IR research. KW: theme, melody, notation index, classical music, database

  12. Barlow, Harold & Morgenstern, Sam (1950). A Dictionary of Opera and Song Themes. New York: Crown Publishers. KW: theme, melody, notation index, classical music, database

  13. Bellini, Pierfrancesco; Nesi, Paolo; & Zoia, Giorgio (2005 October-December). Symbolic music representation in MPEG. IEEE MultiMedia 12(4), pp. 42–49. In the words of a sidebar, "With the spread of computer technology into the artistic fields, new application scenarios for computer-based applications of symbolic music representation (SMR) have been identified. The integration of SMR in a versatile multimedia framework such as MPEG will enable the development of a huge number of new applications in the entertainment, education, and information delivery domains."

  14. Bello, Juan P., Monti, Guliano, & Sandler, Mark (2000). Techniques for Automatic Music Transcription. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000 . KW: audio, monophonic, polyphonic, AMR, segmentation, blackboard

  15. Bello, Juan P.; & Pickens, Jeremy (2005). A Robust Mid-Level Representation for Harmonic Content in Music Signals. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 304–311.

  16. Berenzweig, Adam, Logan, Beth, Ellis, Daniel P.W., & Whitman, Brian (2004). A Large-Scale Evaluation of Acoustic and Subjective Music-Similarity Measures. Computer Music Journal 28(2), pp. 63–76.

  17. Birmingham, W., Dannenberg, R., Wakefield, G., Bartsch, M., Bykowski, D., Mazzoni, D., Meek, C., Mellody, M., & Rand, W. MUSART: Music Retrieval Via Aural Queries. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 73–81. KW: representation, theme extraction, abstraction, Markov model, thematic index, system architecture, melodic contour, audio, phonetic stream, audio thumbnail

  18. Birmingham, William; Pardo, Bryan; Meek, Colin; & Shifrin, Jonah (2002). The MusArt Music-Retrieval System. D-Lib Magazine 8(2); retrieved October 20, 2006, from the World Wide Web: http://www.dlib.org/dlib/february02/birmingham/02birmingham.html.

  19. Birmingham, W., O'Malley, K., Dunn, J.W., & Scherle, R. (2003). V2V: A Second Variation on Query-by-Humming. Demo at JCDL 2003; retrieved March 20, 2006, from the World Wide Web: http://variations2.indiana.edu/pdf/JCDL2003Demo-web.pdf. One of the very few published accounts of systems that combine content-based and metadata-based retrieval of music.

  20. Boltz, M. (1999). The Processing of Melodic and Temporal Information: Independent or Unified Dimensions? Journal of New Music Research 28(1), pp. 67–79.

  21. Brett, Philip; & Smith, Jeremy (2001). Computer Collation of Divergent Early Prints in the Byrd Edition. In Hewlett & Selfridge-Field (2001), pp. 251–260. Discusses at some length, with references to previous work, how similar images can be collated by superimposing a partially-transparent version of one on the other, and describes how the application of this technique to copies of early editions of William Byrd from the same print run made it possible to find significant differences.

  22. Brinkman, Alexander (1990). PASCAL Programming for Music Research. Chicago and London: University of Chicago Press. Somewhat dated; for example, he concentrates on programming in PASCAL and encoding music in DARMS, both of which have largely been supplanted by other technology. Nonetheless, thorough and complete, covering everything from how computer hardware works to details of encoding to how to design good programs—and all with an emphasis on music: it was originally written as a textbook for a graduate course in computer-assisted music research. All in all, still a unique and valuable book.

  23. Brook, Barry, ed. (1970). Musicology and the Computer; Musicology 1966-2000: A Practical Program. New York: City University of New York Press. Includes papers from two groundbreaking symposia held by the American Musicological Society/Greater New York Chapter, in the spring of 1965. One was on music input "languages", covering Ford-Columbia (DARMS), Plaine and Easie, ALMA, and MUSTRAN; the other was on music analysis and documentation. The Preface comments that the earlier was probably "the first full-scale meeting of musicologists on the subject of computer applications." (The volume also includes papers from the "practical program" symposium mentioned.)

  24. Burgoyne, J. Ashley; & McAdams, Stephen (2007). Non-linear Scaling Techniques for Uncovering the Perceptual Dimensions of Timbre. In Proceedings of the 2007 International Computer Music Conference (ICMC 2007), pp. I-73–76.

  25. Byrd, Donald (1994). Music Notation Software and Intelligence. Computer Music Journal 18(1), pp. 17–20; retrieved (in scanned form) May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/MusNotSoftware+Intelligence.pdf. KW: CMN, music formatting, artificial intelligence, counterexample, FAHQMN

  26. Byrd, Donald (2001). Music-Notation Searching and Digital Libraries. In Proceedings of Joint Conference on Digital Libraries (JCDL 2001), pp. 239–246; retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/MusicSearchingViaCMN.pdf . KW: CMN, music IR, searching, music library. Describes NightingaleSearch, still one of the very few attempts to integrate content-based music retrieval with a high-quality notation program.

  27. Byrd, Donald (2004). Variations2 Guidelines For Encoded Score Quality. Retrieved May 20, 2013, from the World Wide Web: http://variations2.indiana.edu/system_design.html

  28. Byrd, Donald (2007). A Similarity Scale for Content-Based Music IR. Retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/MusicSimilarityScale.HTML

  29. Byrd, Donald (2007). Musical Themes and Occurrences of Melodic Confounds. Retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/ThemesAndConfoundsNoTabs.txt

  30. Byrd, Donald (2008). Chart of Candidate Music IR Test Collections. Retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/MusicTestCollections.HTML

  31. Byrd, Donald (2009). Studying Music is Difficult and Important: Challenges of Music Knowledge Representation. In Proceedings of Dagstuhl Seminar on Knowledge Representation for Intelligent Music Processing, Leibniz-Center for Informatics, Wadern, Germany; retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/MusicIsDifficult+Important.doc .

  32. Byrd, Donald (2009). Written Vs. Sounding Pitch. MLA Notes 66,1 (September 2009). Retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/WrittenVsSoundingPitch.doc . The "transposition" relationship between the way a note is written and the pitch at which it sounds is far more complex than is usually believed. This is an updated and expanded version of a Variations2 design paper, with many musical examples added.

  33. Byrd, Donald (2010). Extremes of Conventional Music Notation. Retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/CMNExtremes.htm . KW: CMN, limits, earliest usage. For many years, the author has been compiling this list of "extreme" values for many aspects of music expressed in conventional Western notation: shortest and longest note durations, most complex tuplet, slowest and fastest tempo marks, earliest use of fff, etc. It now includes records in about 70 general categories and about 30 earliest-use categories.

  34. Byrd, Donald, & Crawford, Tim (2002). Problems of Music Information Retrieval in the Real World. Information Processing and Management 38, pp. 249–272; retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/RealWorldMusicIR35TR.pdf . KW: music IR, searching, representation, audio, CMN, MIDI, music perception, polyphony, segmentation, unit of meaning

  35. Byrd, Donald, & Isaacson, Eric (2003). Music Representation in a Digital Music Library. In Proceedings of Joint Conference on Digital Libraries (JCDL 2003), pp. 234–236.

  36. Byrd, Donald, & Isaacson, Eric (2010). A Music Representation Requirement Specification for Academia. Computer Music Journal 27, no. 4 (2003), pp. 43–57; revised version retrieved May 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/MusicRepReqForAcad.doc. KW: CMN, MIDI, representation, SMDL domain, tuplet. Attempts to classify and list, in terms of information represented, all symbols in CWMN (conventional Western music notation) that are significant in terms of making the music readable, strongly emphasizing "classical" music. Also includes some non-notational features of music like voice/part relationships and MIDI patches, plus analytic symbols, e.g., for Schenkerian graphs; but the authors intentionally exclude items that are largely relevant only to publishing, for example, system breaks and page breaks. Most of the article is a long table of features, over 200 in 23 categories, with ratings of importance for academic musicians. This is the only serious attempt I know of to systematically list CWMN symbols for any purpose, with the possible exceptions of the "Dagstuhl Core" and the lists implied in DTDs and schemas for encoding systems like MEI and MusicXML.

  37. Cambouropoulos, Emilios (1998). Musical Parallelism and Melodic Segmentation. In Proceedings of the XII Colloquio di Informatica Musicale, Gorizia, Italy.

  38. Cambouropoulos, Emilios (2008). Voice and Stream: Perceptual and Computational Modeling of Voice Separation. Music Perception 26(1), pp. 75–94.

  39. Cannam, Chris; Landone, Christian; Sandler, Mark; & Bello, Juan Pablo (2006). The Sonic Visualiser: A Visualisation Platform for Semantic Descriptors from Musical Signals. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 324–327.

  40. Casey, Michael (2005, December). Acoustic and Symbolic Lexemes for Organizing Internet Audio. Contemporary Music Review 24(6). KW: audio mosaicing, audio search engine, indexing, n-gram

  41. Casey, Michael, & Crawford, Tim (2004). Automatic Location and Measurement of Ornaments in Audio Recordings. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 311–317.

  42. Casey, Michael, & Slaney, Malcolm (2006). Song Intersection by Approximate Nearest Neighbor Search. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 144–149.

  43. Casey, Michael, & Smaragdis, Paris (1996). Netsound: Structured Audio Encoding and Rendering. In Proceedings of the International Computer Music Conference, Hong Kong, September, 1996.

  44. Castan, Gerd (2005). Music Notation Links. Retrieved March 20, 2008, from the World Wide Web: http://www.music-notation.info/en/compmus/. Another unique and valuable resource. Despite the modest title, includes a substantial amount of information of Castan's own as well as a very large collection of links. Sections include "Musical fonts", "Music notation", "Musical notation codes", "Music notation programs", "Optical Music Recognition", "Audio to MIDI", etc.

  45. Celma, Oscar (2006). Foafing the Music: Bridging the semantic gap in music recommendation. The Semantic Web - ISWC 2006, pp. 927–934.

  46. Chafe, Chris; Mont-Reynaud, Bernard; Rush, Loren (1982). Toward an Intelligent Editor of Digital Audio: Recognition of Musical Constructs. Computer Music Journal 6(1), pp. 30–41. The earliest publication I know of on the subject. Part one of a two-part series (the second part appears in the same journal issue).

  47. Chai, Wei, & Vercoe, Barry. Using User Models in Music Information Retrieval Systems (2000). Poster at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000 .

  48. Charles, Jean-Francois. A Tutorial on Spectral Sound Processing Using Max/MSP and Jitter. Computer Music Journal 32(3), pp. 87–102. More precisely, this is both a tutorial on manipulating spectral (frequency domain) sound data as matrices, and a tutorial on graphical techniques for spectral sound processing with Max/MSP and Jitter.

  49. Chen, A.L.P., & Chen, J.C.C. (1998). Query by Rhythm: An Approach for Song Retrieval in Music Databases. Proceedings of the Institute of Electrical and Electronic Engineers Eighth International Workshop on Research Issues in Data Engineering: Continuous-Media Databases and Applications (RIDE), pp. 139–146.

  50. Chew, Elaine, & Wu, Xiaodan (2004). Separating Voices in Polyphonic Music: A Contig Mapping Approach. Proceedings of the International Symposium on Computer Music Modeling and Retrieval (CMMR 2004); Springer Verlag Lecture Notes in Computer Science no. 3310.

  51. Chew, Elaine, & Yun-Ching Chen (2005). Real-Time Pitch Spelling Using the Spiral Array. Computer Music Journal 29(2), pp. 61–76.

  52. Chordia, Parag (2005). Segmentation and Recognition of Tabla Strokes. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 107–114.

  53. Cilibrasi, Bret; Vitanyi, Paul; & Wolf, Ronald de (2005). Algorithmic Clustering of Music Based on String Compression. Computer Music Journal 28(4), pp. 49–67.

  54. Clifford, Raphael; Christodoulakis, Manolis; Crawford, Tim; Meredith, David; & Wiggins, Geraint (2006). A Fast, Randomised, Maximal Subset Matching Algorithm for Document-Level Music Retrieval. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 150–155. Describes the authors' MSM matching algorithm, which represents notes as a set of points in space. The paper argues convincingly that, for typical symbolic music-IR problems, representing music geometrically is likely to give much better results than the more common symbol strings, especially where polyphony is involved (as it usually is).

  55. Clifford, Raphael, Groult, Richard, Illiopoulos, Costas S., & Byrd, Donald (2004). Music Retrieval Algorithms for the Lead Sheet Problem. In Proceedings of Sound and Music Computing (SMC 2004), Paris, France, October 2004, pp. 141–146.

  56. Collins, Nick (2006, Winter). Composing to Subvert Content Retrieval Engines. ICMA Array, Winter 2006, pp. 37–41. A badly-needed exposition, written in satirical style, of a fundamental but little-understood challenge of many problems of music informatics. Music is, of course, an art form, and the composer/artist can use its elements any way they like—for example, to confound music-IR systems. Obviously, very few composer/artists have that goal in mind; but a great many try to use its elements in new and original ways. This (among other things) makes content-based retrieval a great deal harder with music than with expository prose, the type of text that text-retrieval systems usually deal with and that music retrieval is usually compared to. Similarly, there's a story that Marc Chagall said, in response to criticism of his drawing by an art critic, "Of course I draw poorly. I like to draw poorly." That is, in his art, Chagall had no intention of using the element of drawing the way it was ordinarily used.

  57. Conklin, Darrell; & Bergeron, Mathieu (2008). Feature Set Patterns in Music. Computer Music Journal 32(1), pp. 60–70.

  58. Cook, Nicholas (2005). Towards the Compleat Musicologist? Invited talk, 6th International Conference on Music Information Retrieval (ISMIR 2005). Retrieved May 10, 2008, from the World Wide Web: http://ismir2005.ismir.net/documents/Cook-CompleatMusicologist.pdf

  59. Cooke, Deryck (1959). The Language of Music. Oxford, U. K.: Oxford University Press. In the words of Hofstadter (1980), "The only book that I know which tries to draw an explicit connection between elements of music and elements of human emotion. A valuable start down what is sure to be a long hard road to understanding music and the human mind."

  60. Cooper, Matthew; Foote, Jonathan; Pampalk, Elias; & Tzanetakis, George (2006). Visualization in Audio-Based Music Information Retrieval. Computer Music Journal 30(2), pp. 42–62.

  61. Cope, David (2003). Computer Analysis of Musical Allusions. Computer Music Journal 27(2), pp. 11–28.

  62. Crawford, Tim (2005). Music Information Retrieval and the future of Musicology. Technical report. Retrieved May 10, 2007, from the World Wide Web: http://www.ocve.org.uk/content/reports/index.html

  63. Crawford, Tim (2006). After the search is over ... the work begins. In Dagstuhl Seminar Proceedings, Tim Crawford and Remco C. Veltkamp, eds. Dagstuhl: Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany. KW: Music information retrieval; musicology; OMRAS; harmonic modeling.

  64. Crawford, Tim, & Byrd, Donald (1997). Musical Data Retrieval using Multiple Indexes. Paper read at IMS Study Group on Musical Data and Computer Applications, Musical Data Retrieval: Techniques and Interfaces, King’s College, London.

  65. Crawford, Tim, Iliopoulos, C.S., & Raman, R. (1998). String-Matching Techniques for Musical Similarity and Melodic Recognition. In Hewlett & Selfridge-Field (1998).

  66. Cronin, Charles (1998). Concepts of Melodic Similarity in Music-Copyright Infringement Suits. In Hewlett & Selfridge-Field (1998), pp. 187–210. KW: copyright infringement, IPR, public domain.

  67. Cronin, Charles (2002). The Music Plagiarism Digital Archive at Columbia Law Library. In Proceedings of WEDELMUSIC '02. KW: copyright infringement, IPR, public domain.

  68. Cronin, Charles (2008). Columbia Law School & UCLA Law School Copyright Infringement Project (formerly the Columbia Music Plagiarism Project). Retrieved December 10, 2008, from the World Wide Web: http://cip.law.ucla.edu/entrance.html. In its own words, this remarkable website "comprises hundreds of documents (texts, scores, audio and video files) associated with music copyright infringement cases in the United States from 1845 forward." KW: copyright infringement, IPR, public domain

  69. de la Cuadra, Patricio; Master, Aaron; & Sapp, Craig (2001). Efficient Pitch Detection Techniques for Interactive Music. In Proceedings of International Computer Music Conference (ICMC 2001), La Habana, Cuba. Retrieved September 20, 2007, from http://ccrma.stanford.edu/~pdelac/research/index.html

  70. Dannenberg, Roger (1993). Music Representation Issues, Techniques, and Systems. Computer Music Journal 17(3), pp. 20–30. KW: heirarchy, multiple heirarchies, MIDI, extensibility, Music V, real time, metric time, music notation, continuous vs. discrete, declarative vs. procedural, coding

  71. Dannenberg, Roger (2001). Music Information Retrieval as Music Understanding. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 139–142. KW: music perception, computer accompaniment system, score following, dynamic programming

  72. Dannenberg, Roger, Birmingham, W., Tzanetakis, G., Meek, C., Hu, N., & Pardo, B. (2004). The MUSART Testbed for Query-by-Humming Evaluation. Computer Music Journal 28(2), pp. 34–48.

  73. Dannenberg, Roger; & Raphael, Christopher (2006, August). Music score alignment and computer accompaniment. Communications of the ACM 49,8, pp. 39–43. Abstract available at http://doi.acm.org/10.1145/1145287.1145311.

  74. Deutsch, Diana (1972). Octave generalization and tune recognition. Perception and Psychophysics 11(6), pp. 411–412.

  75. Dixon, Simon, & Widmer, Gerhard (2005). MATCH: A Music Alignment Tool Chest. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 492–497.

  76. Donaldson, Justin & Knopke, Ian (2007). Music Recommendation Mapping and Interface Based on Structural Network Entropy. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 181–182.

  77. Doraisamy, Shymala, & Rüger, Stefan (2001). An Approach Towards a Polyphonic Music Retrieval System. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 187–193. KW: index, n-gram, ratio bins, ranking, histogram, experiment

  78. Doraisamy, Shymala, & Rüger, Stefan (2003). Emphasizing the Need for TREC-like Collaboration Towards MIR Evaluation. In The MIR/MDL Evaluation Project White Paper Collection, pp. 90–96.

  79. Doraisamy, Shymala, & Rüger, Stefan (2004). A Polyphonic Music Retrieval System Using N-Grams. In Proceedings of the 5th International Symposium on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 204–209.

  80. Dovey, Matthew (1999). A matrix based algorithm for locating polyphonic phrases within a polyphonic musical piece. In Proceedings of AISB ’99 Symposium on Artificial Intelligence and Musical Creativity. Edinburgh, Scotland: Society for the Study of Artificial Intelligence and Simulation of Behaviour.

  81. Dovey, Matthew (2001). A Technique for "Regular Expression" Style Searching in Polyphonic Music. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 179–185. KW: OMRAS, CMN, piano roll, XML, gap

  82. Dovey, Matthew (2001). Adding content-based searching to a traditional music library catalogue server. In Proceedings of Joint Conference on Digital Libraries (JCDL 2001), pp. 249–250.

  83. Dovey, Matthew (2002). Music GRID – A Collaborative Virtual Organization for Music Information Retrieval Collaboration and Evaluation. In The MIR/MDL Evaluation Project White Paper Collection, pp. 50–52. Retrieved August 20, 2005, from the World Wide Web: http://music-ir.org/evaluation/wp2/wp2_dovey.pdf . KW: OMRAS, WebServices, GRID IR

  84. Dovey, Matthew, & Crawford, Tim (1999). Heuristic Models of Relevance Ranking in Searching Polyphonic Music. In Proceedings of Diderot Forum on Mathematics and Music, Vienna, Austria, pp. 111–123.

  85. Downie, J. Stephen (1999). Evaluating a Simple Approach to Music Information Retrieval: Conceiving Melodic N-Grams as Text (doctoral dissertation, Univ. of Western Ontario).

  86. Downie, J. Stephen, ed. (2003). The MIR/MDL Evaluation Project White Paper Collection, 3rd ed. Retrieved August 20, 2005, from the World Wide Web: http://music-ir.org/evaluation/wp.html

  87. Downie, J. Stephen (2003). Music information retrieval. Annual Review of Information Science and Technology 37, pp. 295–340. Retrieved August 20, 2005, from the World Wide Web: http://music-ir.org/downie_mir_arist37.pdf .

  88. Downie, J. Stephen (2004). The Scientific Evaluation of Music Information Retrieval Systems: Foundations and Future. Computer Music Journal 28(2), pp. 12–23.

  89. Downie, J. Stephen (2006, December). The Music Information Retrieval Evaluation eXchange (MIREX). D-Lib Magazine 12(12); retrieved Sept. 10, 2007, from the World Wide Web: http://www.dlib.org/dlib/december06/downie/12downie.html

  90. Downie, J.S., & Nelson, M. (2000). Evaluation of a Simple and Effective Music Information Retrieval System. In Proceedings of ACM SIGIR 2000 Conference on Research and Development in Information Retrieval. New York: Association for Computing Machinery.

  91. Downie, J. Stephen, et al (2003). The Music Information Retrieval Research Bibliography. Retrieved May 20, 2006, from the World Wide Web: http://music-ir.org/research_home.html .

  92. Downie, J. Stephen, West, Kris, Ehmann, Andreas, & Vincent, Emmanuel (2005). The 2005 Music Information retrieval Evaluation Exchange (MIREX 2005): Preliminary Overview. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 320–323. Retrieved March 25, 2006, from the World Wide Web: http://ismir2005.ismir.net/proceedings/xxxx.pdf.

  93. Droettboom, Michael, Fujinaga, Ichiro, MacMillan, K., Patton, M., Warner, J., Choudhury, G.S., & DiLauro, T. (2001). Expressive and Efficient Retrieval of Symbolic Musical Data. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 173–178. KW: natural-language search engine, GUIDO, Themefinder, MELDEX, melodic search, rhythmic search, simultanaeity, secondary index, partitioning, regular expression

  94. Dubnov, Shlomo (2006). Spectral Anticipations. Computer Music Journal 30(2), pp. 63–83.

  95. Dubnov, Shlomo, McAdams, Stephen, & Reynolds, Roger (2004). Structural and Affective Aspects of Music from Statistical Audio Signal Analysis. To appear in Journal of the American Society for Information Science and Technology, Special Issue on Style, 2004 / 2005. Retrieved May 10, 2006, from the World Wide Web: http://music.ucsd.edu/~sdubnov/ . A unique feature of the research this paper describes is that one of the authors (Reynolds) is a well-known composer, and the research involves a composition of his the structure of which was "conceived to allow experimental exploration of the way in which musical materials and formal structure interact".

  96. Dunn, Jon, & Mayer, Constance (1999). VARIATIONS: A digital music library system at Indiana University. DL '99: In Proceedings of the Fourth ACM Conference on Digital Libraries, pp. 12–19.

  97. Dunn, Jon, & Cowan, William G. (2005). EVIADA: Ethnomusicological Video for Instruction and Analysis Digital Archive. Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries, Denver, Colorado, p. 407.

  98. Dunn, Jon; Byrd, Donald; Notess, Mark; Riley, Jenn; & Scherle, Ryan (2006, August). Variations2: Retrieving and Using Music in an Academic Setting. Communications of the ACM 49,8, pp. 53–59.

  99. Ellis, Daniel P.W. (2006, August). Extracting Information from Music Audio. Communications of the ACM 49,8, pp. 32–37.

  100. Flexer, Arthur; Gouyon, Fabien; Dixon, Simon; & Widmer, Gerhard (2006). Probabilistic Combination of Features for Music Classification. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 111–114.

  101. Flexer, Arthur, Pampalk, Elias, & Widmer, Gerhard (2005). Novelty Detection Based On Spectral Similarity Of Songs. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 260–263.

  102. Foote, Jonathan (2000). ARTHUR: Retrieving Orchestral Music by Long-Term Structure. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved September 10, 2008, from the World Wide Web: http://ciir.cs.umass.edu/music2000

  103. Fremerey, Christian (2006). SyncPlayer - a Framework for Content-Based Music Navigation. Master's Thesis, Dept. of Computer Science, University of Bonn.

  104. Fremerey, Christian; Kurth, Frank; Müller, Meinard; & Clausen, Michael (2007). A Demonstration of the SyncPlayer System. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 131–132.

  105. Fujinaga, Ichiro, & Weiss, Susan Forscher (2004). Music. In Schreibman, Siemens, & Unsworth (2004), pp. 97–107.

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  107. Garton, Brad, & Suttor, Matthew (1998). A Sense of Style. In Proceedings of the 1998 International Computer Music Conference. Retrieved August 20, 2007, from the World Wide Web: http://www.music.columbia.edu/~brad/writing/papes/Sense_of_Style.pdf

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  111. Good, Michael (2001). MusicXML for Notation and Analysis. In Hewlett & Selfridge-Field (2001), pp. 113–124. KW: interchange, music notation, CMN, music representation, XML, MuseData, Humdrum, analysis

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  116. Goto, Masataka (2004). Development of the RWC Music Database. In Proceedings of the 18th International Conference on Acoustics (ICA 2004), pp. I-553–556.

  117. Goto, Masataka, & Goto, Takayuki (2005). Musicream: New Music Playback Interface for Streaming, Sticking, Sorting, and Recalling Musical Pieces. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 404–411.

  118. Grande, Cindy (1997). The Notation Interchange File Format: A Windows-Compliant Approach. In Selfridge-Field (1997), pp. 491–512.

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  121. Hall, Gary (2002, April). Cramped Quarters. Electronic Musician 18(5), pp. 58–74. KW: compression, lossless, lossy, perceptual coding, AAC, MLP, MPEG, MP3

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  123. Harrison, Nate (2004). Can I Get An Amen? Retrieved July 20, 2006, from the World Wide Web: http://nkhstudio.com/pages/popup_amen.html. KW: copyright infringement, IPR

  124. Harte, Christopher, Sandler, Mark, Abdallah, Samer, & Gomez, Emilia (2005). Symbolic Representation of Musical Chords: A Proposed Syntax for Text Annotations. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 66–70.

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  127. Hemmasi, Harriette (2002). Why not MARC? In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), Paris, France, pp. 242–248. Discussion of the factors that led the Variations2 team to abandon the MARC format for bibliographic information that has been the library cataloging standard for decades, and to develop a new metadata model—one that resembles the influential proposed standard FRBR in important ways.

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  132. Hiller, Lejaren, & Isaacson, Leonard (1959). Experimental Music. New York: McGraw-Hill. A lengthy excerpt appears in Sayre & Crosson (1963). Describes the authors' pioneering work on using a computer for musical composition, dating back to the mid-1950's or thereabouts and perhaps the first of its kind. Their work may also be the first on computational models of musical processes of any type. However, the book goes much deeper than this brief description suggests, with comments on aesthetics and the fundamental "logic of musical composition" that are interesting even today.

  133. Hjelte, Garth (2005, November). Lost in Translation. Electronic Musician 21,11, pp. 39–47. How to translate between sound-sample-file formats.

  134. Hofmann-Engl, Ludger (2001). Towards a cognitive model of melodic similarity. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 143–151. KW: similarity models, pitch perception, meloton, transposition, inversion

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  139. Huron, David (1988). Error Categories, Detection, and Reduction in a Musical Database. Computers and the Humanities 22, pp. 253–264. An important, pioneering discussion of the issues the title mentions.

  140. Huron, David (1992). Design Principles in Computer-based Music Representation. In Marsden & Pople (1992), pp. 5–39. Somewhat out-of-date. Also, what he calls "representation" is at least as much encoding as representation. With these caveats -- and failing to distinguish clearly between encoding as representation is not at all unusual -- this is still a useful discussion of principles that underlie representation and encoding, both in general and for music in particular. Includes a list of 12 "properties of a good representation", with detailed comments on each.

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  148. Kapur, Ajay, McWalter, Richard I., & Tzanetakis, George (2005). New Music Interfaces For Rhythm-Based Retrieval. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 130–136.

  149. Kassler, Michael (1966). Toward Musical Information Retrieval. Perspectives of New Music 4(2), pp. 59–67. One of the first published articles on music IR of any kind.

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  151. Kilian, Jürgen, & Hoos, Holger (2004). MusicBLAST—Gapped Sequence Alignment for MIR. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), pp. 38–41. Describes MusicBLAST, an algorithm for approximate pattern searching and matching on symbolic music data, based on the BLAST algorithm for similarity search on biological sequence data.

  152. Knopke, Ian (2008). The Perlhumdrum and Perllilypond Toolkits for Symbolic Music Information Retrieval. In Proceedings of the 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, pp. 147–152.

  153. Knopke, Ian & Byrd, Donald (2007). Towards MusicDiff: A Foundation for Improved Optical Music Recognition using Multiple Recognizers. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 123–126.

  154. König, Sven (2006). sCrAmBlEd?HaCkZ!. Retrieved July 20, 2006, from the World Wide Web: http://www.popmodernism.org/scrambledhackz/. "Gramophone records, magnetic tapes, vinyl records, digital samplers and computers have already liberated the samples long ago. But still - to infringe copyrights - one has to decide which sample one actually wants to steal. One has to arduously load audio files into sample editors or sequencers. One has to cut, copy, paste and arrange. All that takes precious creative energy and a lot of time. Enough of that! Copyright infringements have never been easier than with sCrAmBlEd?HaCkZ!" The demo video on the site does a great job of explaining what sCrAmBlEd?HaCkZ is about, and he's not kidding; however, it's really a tool for improvising video (including music video) performances based on pre-existing material, regardless of the legal status of that material. KW: copyright infringement, IPR, sound signature, audio mosaicing

  155. Kornstaedt, Andreas (2001). The JRing System for Computer-Assisted Musicological Analysis. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 93-98. KW: musicology, graphical user interface, Humdrum, software, catalogue, customization

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  194. Moore, F. Richard (1990). Elements of Computer Music. Englewood Cliffs, N.J.: Prentice-Hall. Clearly and concisely describes how to analyze, process and synthesize musical structures and sounds by computer, going into a fair amount of detail; includes a substantial amount of code, nearly all in C, and some complete programs. It should be accessible to a technically-minded reader with limited background, since Moore includes material on acoustics and digital audio as well as appendices on mathematics, units of measure, tuning, and the cmusic language. Despite its age, a very valuable book.

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  211. Pampalk, Elias, Dixon, Simon, & Widmer, Gerhard (2004). Exploring Music Collections by Browsing Different Views. Computer Music Journal 28(2), pp. 49–62. Describes a very promising approach to visualizing and browsing music collections, based on Self-Organizing Maps (SOMs) focused on information derived from audio analysis and/or metadata. An important feature is that multiple maps of the same collection are aligned so the user can explore different aspects by gradually changing focus from one view to another.

  212. Pampalk, Elias, Rauber, Andreas, & Merkl, Dieter (2002?). Content-based Organization and Visualization of Music Archives. In Proceedings of the ACM Conference on Multimedia, Juan les Pins, France. KW: visualization, genre classification, rhythm patterns, self-organizing map, feature extraction, Smoothed Data Histograms, Islands of Music

  213. Pardo, Bryan (2005). Probabilistic Sequence Alignment Methods for On-Line Score Following of Music Performances. Doctoral dissertation, Department of Computer Science & Engineering, University of Michigan. Of all the music-alignment research I know of, Pardo's as described here uses the largest amount of "score-level" symbolic information: in addition to note pitch and rhythm, his representation includes chord symbols, key signatures, section marks, repeat signs, and skips.

  214. Pardo, Bryan, & Birmingham, William (2002). Encoding Timing Information for Musical Query Matching. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), Paris, France, pp. 267–268. KW: IOI, quantization, alphabet size, bins

  215. Pardo, Bryan, & Birmingham, William (2003). Query by Humming: How good can it get? In The MIR/MDL Evaluation Project White Paper Collection, pp. 107–109.

  216. Pardo, Bryan, & Sanghi, Manan (2005). Polyphonic Musical Sequence Alignment for Database Search. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 215–222.

  217. Parsons, Denys (1975). The Directory of Tunes and Musical Themes. Cambridge, England: Spencer Brown. An index to thousands of themes via melodic contour alone -- melodies are described as series of ups, downs, and repeats -- intended especially for people with little musical training.

  218. Peeters, Geoffroy (2004). A Large Set of Audio Features for Sound Description (Similarity and Classification) in the CUIDADO Project. Retrieved June 10, 2007, from the World Wide Web: www.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf

  219. Peeters, Geoffroy; Burthe, Amaury; & Rodet, Xavier (2002). Toward Automatic Music Audio Summary Generation from Signal Analysis. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp. 94–100.

  220. Pickens, Jeremy (2000). A Comparison of Language Modeling and Probabilistic Text Information Retrieval Approaches to Monophonic Music Retrieval. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000 . KW: symbolic music, probabilistic retrieval, Bayesian inference network, n-gram, known-item search

  221. Pickens, Jeremy; Bello, Juan P.; Crawford, Tim; Dovey, Matthew; Monti, Guliano; Sandler, Mark B., & Byrd, Donald (2002). Polyphonic Score Retrieval Using Polyphonic Audio Queries: A Harmonic Modeling Approach. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), Paris, France, pp. 140–149.

  222. Pickens, Jeremy (2003). Tracks and Topics: Ideas for Structuring Music Retrieval Test Collections and Avoiding Balkanization. In The MIR/MDL Evaluation Project White Paper Collection, pp. 110–113. KW: evaluation, Cranfield model, TREC, MusicGrid

  223. Pickens, Jeremy (2004). Harmonic Modeling for Polyphonic Music Retrieval. Doctoral dissertation, Department of Computer Science, University of Massachusetts.

  224. Pickens, Jeremy (2005). Classifier Combination for Capturing Musical Variation. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 648–651.

  225. Pohlmann, Ken (2005). Principles of Digital Audio, Fifth Edition. New York: McGraw-Hill. A highly readable standard text on the subject that goes into considerable technical detail in its 800-plus pages; however, "the subject" is really digital audio engineering. Much of it is devoted to details of hardware (CDs, DATs, DVDs, etc.) of little interest for music IR or informatics. On the other hand, it has the most comprehensive section I've seen -- nearly 100 pages -- on all aspects of perceptual coding (from psychoacoustic principles to the design and evaluation of lossy compression systems like MP3, AAC), fundamentals of digital audio, "desktop audio" (formats, protocols, etc.) and other very relevant topics. It also has an extensive bibliography.

  226. Pope, Stephen Travis; Holm, Frode; & Kouznetsov, Alexandre (2004). Feature Extraction and Database Design for Music Software. In Proceedings of the 2004 International Computer Music Conference (ICMC 2004).

  227. Pope, Stephen Travis; & Rossum, Guido van (1995, Spring). Machine Tongues XVIII: A Child's Garden of Sound File Formats. Computer Music Journal 19,1.

  228. Proutskova, Polina (2007). Musical Memory of the World -- Data Infrastructure in Ethnomusicological Archives. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 161–162.

  229. Purwins, Hendrik (2005). Profiles of Pitch Classes - Circularity of Relative Pitch and Key: Experiments, Models, Music Analysis, and Perspectives. Doctoral dissertation. Retrieved December 26, 2005, from the World Wide Web: http://opus.kobv.de/tuberlin/volltexte/2005/1085/ . "The doubly-circular inter-relation of the major and minor keys on all twelve pitch classes can be depicted in toroidal models of inter-key relations (TOMIR). We demonstrate convergence of derivations on the explanatory levels of a) an experiment in music psychology, b) geometrical considerations in music theory, and c) computer implementation of musical listening scenarios."

  230. Raimond, Yves, & Sandler, Mark (2008). A Web of Musical Information. In Proceedings of the 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, pp. 263–268.

  231. Raphael, Christopher (2001). Automated Rhythm Transcription. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 99-107. KW: stochastic model, tempo tracking, Markov chain

  232. Raphael, Christopher (2004). A Hybrid Graphical Model for Aligning Polyphonic Audio with Musical Scores. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 387-394.

  233. Raphael, Christopher (2008). A Classifier-Based Approach to Score-Guided Source Separation of Musical Audio. Computer Music Journal 32(1), pp. 51–59.

  234. Raphael, Christopher, & Stoddard, Joshua (2004). Functional Harmonic Analysis Using Probabilistic Models. Computer Music Journal 28(3), pp. 45–52.

  235. Rice, Stephen V., & Bailey, Stephen M. (2004). Searching for Sounds. Retrieved December 10, 2008, from the World Wide Web: http://www.comparisonics.com/SearchingForSounds.html .

  236. Riley, Jenn (2005). Exploiting Musical Connections: A Proposal for Support of Work Relationships in a Digital Music Library. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 123–129. Works that are derived from or part of another work are common in many musical traditions; however, very few music IR systems, even those with an academic and bibliographic slant, take advantage of them. This paper describes research into these relationships and suggests how they could be used, esepcially with Western art music.

  237. Riley, Jenn & Mayer, Constance A. (2006). Ask a Librarian: The Role of Librarians in the Music Information Retrieval Community. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 13–18.

  238. Rink, John, et al (2004). Online Chopin Variorum Edition — Pilot Project: Final Report. Retrieved December 28, 2005, from the World Wide Web: http://www.ocve.org.uk/content/reports/index.html

  239. Roads, Curtis (1985). Grammars as Representations for Music. In Roads & Strawn (1985).

  240. Roads, Curtis, & Strawn, John, eds. (1985). Foundations of Computer Music. Cambridge, Massachusetts: MIT Press.

  241. Roads, Curtis, with John Strawn, Curtis Abbott, John Gordon, & Philip Greenspun (1996). The Computer Music Tutorial. Cambridge, Massachusetts: MIT Press. From the Preface: "The Computer Music Tutorial addresses the need for a standard and comprehensive text of basic information on the theory and practice of computer music... [T]his textbook contains all new material directed towards teaching purposes." With the understanding that "computer music" refers largely to applications of computers to creative purposes, this work of over 1200 pages is about as comprehensive as a single volume can be; it is also authoritative, since the main author is a distinguished expert in the field. However, as the publication date suggests, it's no longer completely up-to-date. In addition, as compared to the even older book of Moore (1990), it contains much less usable code, and doesn't contain all the background material in Moore's appendices.

  242. Roland, Perry (2002). The Music Encoding Initiative (MEI). In Proceedings of MAX 2002: First International Conference on Musical Applications using XML, pp. 55–59. KW: Text Encoding Initiative (TEI), Music Encoding Initiative (MEI), music notation, CMN, music representation, XML, DTD design

  243. Roland, Perry and Downie, J. Stephen (2007). Recent Developments in the Music Encoding Initiative Project: Enhancing Digital Musicology and Scholarship. Digital Humanities 2007 abstract; retrieved February 10, 2011, from the World Wide Web: http://www.digitalhumanities.org/dh2007/abstracts/xhtml.xq?id=223

  244. Rust, Ted (1995). Seeing Music: The Art Of Stephen Malinowski. Music For the Love of It, October 1995. Retrieved February 17, 2004, from the World Wide Web: http://www.well.com/user/smalin/rustarticle.html . KW: visualization, bar graph, score, harmony

  245. Ryynanen, Matti, & Klapuri, Anssi (2008 Fall). Automatic Transcription of Melody, Bass Line, and Chords in Popular Music. Computer Music Journal 32,3, pp. 72–86.

  246. Sapp, Craig Stuart (2001). Harmonic Visualizations of Tonal Music. In Proceedings of the 2001 International Computer Music Conference, pp. 423–430.

  247. Sapp, Craig Stuart (2005). Online Database of Scores in the Humdrum File Format. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 664–665.

  248. Sapp, Craig Stuart (2007). Comparative Analysis of Multiple Musical Performances. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 497–500.

  249. Schedl, Markus, Knees, Peter, & Widmer, Gerhard (2005). Discovering and Visualizing Prototypical Artists by Web-based Co-Occurrence Analysis. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 21–28.

  250. Scherle, Ryan, & Byrd, Donald (2004). The Anatomy of a Bibliographic Search System for Music. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 489–496; retrieved December 10, 2008, from the World Wide Web: http://variations2.indiana.edu/pdf/ismir04search.pdf

  251. Schwartz, Baron (2003). Music Notation as a MEI Feasability Test. ISMIR 2003 poster.

  252. Seeger, Charles (1958, April). Prescriptive and Descriptive Music Writing. Musical Quarterly 44(2), pp. 184–195. A penetrating and readable critique by a pioneering ethnomusicologist of the "hazards...inherent in our practices of writing music", specifically of conventional music notation as a means of describing music for scientific purposes. Seeger calls for a more purely graphic form of writing music, a line of thought which lead to the creation of his famous melograph.

  253. Selfridge-Field, Eleanor, ed. (1997). Beyond MIDI: The Handbook of Musical Codes. Cambridge, Mass.: MIT Press. Includes chapters on "Sound-Related Codes" (MIDI, MIDI files and several extensions to them, Csound, etc.); "Musical Notation Codes" (DARMS and extensions, SCORE, Lime Tilia, Nightingale Notelist, Braille); "Codes for Data Management and Analysis" (Essen, Plaine and Easie, Humdrum and kern, MuseData); "Interchange Codes" (SMDL, NIFF, etc.); etc.

  254. Selfridge-Field, Eleanor (1997). Describing Musical Information. In Selfridge-Field (1997), pp. 3–38.

  255. Selfridge-Field, Eleanor (1998). Conceptual and Representational Issues in Melodic Comparison. In Hewlett, W., & Selfridge-Field, E. (Eds.), Melodic Similarity: Concepts, Procedures, and Applications (Computing in Musicology 11) (pp. 3–64). Cambridge, Massachusetts: MIT Press.

  256. Shazam Entertainment Ltd. (2005). Shazam — discover music — share music — get music. Retrieved December 20, 2005, from the World Wide Web: http://www.shazam.com/music/portal/ . The first successful commercial service to identify recordings (via audio fingerprints); as their web site used to say, "just hit 2580 on your mobile phone and identify music".

  257. Shenoy, Arun & Wang, Ye (2005, September). Key, Chord, and Rhythm Tracking of Popular Music Recordings. In Computer Music Journal 29(3), pp. 75–86.

  258. Sloan, Donald (1993). Aspects of Music Representation in HyTime/SMDL. Computer Music Journal 17(4), pp. 51–59.

  259. Sloan, Donald (1997). HyTime and Standard Music Description Language: A Document-Description Approach. In Selfridge-Field (1997), pp. 469–490.

  260. Smith, Julius O. (2003). Mathematics of the Discrete Fourier Transform (DFT), with Music and Audio Applications. W3K Publishing. Retrieved July 20, 2006, from the World Wide Web: http://ccrma.stanford.edu/~jos/mdft/ . In the words of the Preface, "This book started out as a series of readers for my introductory course in digital audio signal processing that I have given at the Center for Computer Research in Music and Acoustics (CCRMA) since 1984. The course was created primarily for entering Music Ph.D. students in the Computer Based Music Theory program at CCRMA. As a result, the only prerequisite is a good high-school math background, including some calculus exposure."

  261. Smith, L.A., McNab, R.J., & Witten, I.H. (1998). Sequence-Based Melodic Comparison: A Dynamic Programming Approach. In Hewlett, W., & Selfridge-Field, E. (Eds.), Melodic Similarity: Concepts, Procedures, and Applications (Computing in Musicology 11). Cambridge, Massachusetts: MIT Press.

  262. Smithers, Brian (2005, March). Square One: A Stitch in Time: Manipulating Time and Pitch for Fun and Profit. Electronic Musician 21,3, pp. 82–84.

  263. Stanley, Jim, & Kearns, Antony (2001). The HymnQuest Software: A DARMS Parser for Hymn-Tune Searching. In Hewlett & Selfridge-Field (2001), pp. 207–215. Describes what was probably the first commercial product to incorporate music-IR technology, namely a database of melodies in symbolic form with an engine for searching it.

  264. Sterian, A., Simoni, M. H., & Wakefield, G. H. (1999). Model-based Musical Transcription. Proceedings of the 1999 International Computer Music Conference (Beijing, China). Retrieved August 23, 2004, from the World Wide Web: http://musen.engin.umich.edu/papers/transcription.pdf

  265. Stewart, Darin (2002, July). The Digital-Rights Debate: Can you protect your rights without alienating your audience? Electronic Musician 18(8), pp. 110–120. KW: electronic distribution, digital-rights management (DRM), license broker, license predelivery/postdelivery, Secure Audio Path (SAP), digital watermarking, Fair Use, XrML, ODRL

  266. Stewart, Darin (2003, December). XML for Music. Electronic Musician 19(13), pp. 58–64.

  267. Stolet, Jeffery (2009, March). Discovering MAX: Getting Started with Cycling 74's MAX Graphical Programming Software. Electronic Musician 25(3), pp. 38–42.

  268. Suyoto. Iman S.H., & Uitdenbogerd, A.L. (2004). Exploring Microtonal Matching. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 224–231.

  269. Talbot, Michael, ed. (2000). The Musical Work: Reality or Invention? Liverpool: Liverpool University Press.

  270. Temperley, David (2004). An Evaluation System for Metrical Models. Computer Music Journal 28(3), pp. 28–44.

  271. Temperley, David (2006). The Cognition of Basic Musical Structures. Cambridge, Mass.: MIT Press. The only substantial work I know of that combines principled approaches (including music theory as well as psychology) and "ad hoc" computational approaches to problems of music cognition. While it focuses primarily on "classical" music, the book also discusses rock and African music at some length. Temperley primarily uses preference-rule systems implemented with dynamic programming, and he includes an unusually clear explanation of how dynamic programming works.

  272. Temperley, David (2007). Music and Probability. Cambridge, Mass.: MIT Press. I'm not yet familiar with this book, but it seems likely to be the second "substantial work" meeting the criteria I describe for his The Cognition of Basic Musical Structures.

  273. Teodoru, Gabi & Raphael, Christopher (2007). Pitch Spelling with Conditionally Independent Voices. In Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, pp. 201–206.

  274. Thomas, Verena; Fremerey, Christian; Müller, Meinard; & Clausen, Michael (2012). Linking Sheet Music and Audio: Challenges and New Approaches. In Müller, Goto, & Schedl (2012).

  275. Tintarev, Nava & Masthoff, Judith (2007). A Survey of Explanations in Recommender Systems. In G Uchyigit (ed.), Workshop on Recommender Systems and Intelligent User Interfaces associated with ICDE'07, Istanbul, Turkey.

  276. Tseng, Y.-H. (1999). Content-based Retrieval for Music Collections. In Proceedings of ACM SIGIR 1999 Conference on Research and Development in Information Retrieval, pp. 176–182. New York: Association for Computing Machinery.

  277. Typke, Rainer (2006). MIR Systems: A Survey of Music Information Retrieval Systems. Retrieved January 14, 2006, from the World Wide Web: http://mirsystems.info

  278. Typke, Rainer (2007). Music Retrieval based on Melodic Similarity. This is the author's very interesting PhD work. Self-published; available from Lulu.com (http://www.lulu.com/content/456082).

  279. Typke, Rainer, Wiering, Frans, & Veltkamp, Remco C. (2004). A Search Method for Notated Polyphonic Music with Pitch and Tempo Fluctuations. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 281–288. KW: transportation distance, RISM A/II, segmentation, vantage indexing

  280. Typke, Rainer, Wiering, Frans, & Veltkamp, Remco C. (2005). A Survey of Music Information Retrieval Systems. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 153–160. An overview of 17 existing systems for content-based retrieval of music in both audio and symbolic forms. Includes a "map" of the systems showing the tasks and users for which each system seems most appropriate; the "task" axis is similar in intent to Byrd's "Similarity Scale for Content-Based Music IR". The authors argue that one can see from the map that these systems "fail to cover a gap between the very general and very specific retrieval tasks."

  281. Tzanetakis, George, & Cook, Perry (2000). Audio Information Retrieval (AIR) Tools. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000 . KW: MARSYAS, feature-based audio analysis, classification, segmentation, audio thumbnailing, TimbreGram, principal component analysis (PCA)

  282. Tzanetakis, George, Essl, Gerog, & Cook, Perry (2001). Automatic Genre Classification of Audio Signals. In Proceedings of the Second International Symposium on Music Information Retrieval (ISMIR 2001), pp. 99–107. KW: texture, instrumentation, rhythmic structure, rhythmic strength, heirarchic classification, surface features, user interface, MARSYAS

  283. Tzanetakis, George, Gao, Jun, & Steenkiste, Peter (2004). A Scalable Peer-to-Peer System for Music Information Retrieval. Computer Music Journal 28(2), pp. 24–33.

  284. Uitdenbogerd, A.L., & Zobel, J. (1998). Manipulation of music for melody matching. In Proceedings of ACM International Conference on Multimedia, pp. 235–240. New York: Association for Computing Machinery.

  285. Uitdenbogerd, A.L., Chattaraj, A., & Zobel, J. (2000). Music Information Retrieval: Past, Present and Future. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000 .

  286. Uitdenbogerd, A.L., & Yap, Yah Wah (2003). Was Parsons Right? An experiment in usability of music representations for melody-based music retrieval. In Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR 2003), Baltimore, Maryland, pp. 75–79. Reports on an interesting study, intended to test the hypothesis of Parsons (1975) that people with little musical training would be able to identify music by melodic contour alone. The authors conclude that "unfortunately the directory is beyond the capabilities of its target audience", and of only limited value to those with stronger musical backgrounds.

  287. Ukkonen, Esko; Lemström, Kjell; & Mäkinen (2003). Geometric Algorithms for Transposition-Invariant Content Based Music Retrieval. In Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR 2003), pp. 193–199.

  288. Variations2 (2006). Variations2: IU Digital Music Library Project. Retrieved December 20, 2006, from the World Wide Web: http://variations2.indiana.edu/research/. KW: system architecture, metadata standards, component-based architecture, network services, human-computer interaction (HCI), intellectual property rights (IPR)

  289. Viro, Vladimir (2011). Peachnote: Music Score Search and Analysis Platform. In Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), pp. 359–362.

  290. Voorhees, Ellen (2002). Whither Music IR Evaluation Infrastructure: Lessons to be Learned from TREC. The MIR/MDL Evaluation Project White Paper Collection, pp. 7–13.

  291. Walmsley, Paul (1999). Bayesian Graphical Models for Polyphonic Pitch Tracking. In Proceedings of Diderot Forum on Mathematics and Music, Vienna, Austria. Retrieved January 31, 2001, from the World Wide Web: http://www-sigproc.eng.cam.ac.uk/~pjw42/ftp/didlt.pdf

  292. Wang, Avery (2003). An Industrial-Strength Audio Search Algorithm. In Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR 2003), Baltimore, Maryland, pp. 7–14. Version with audio examples retrieved January 31, 2004, from the World Wide Web: http://ismir2003.ismir.net/presentations.html . A description of the audio-fingerprinting algorithm behind Shazam, with some amazing audio examples of how it works in practice.

  293. Wattenberg, Martin (2004). The Shape of Song. Retrieved July 20, 2004, from the World Wide Web: http://www.turbulence.org/Works/song/index.html. KW: Java, visualization, musical structure, MIDI file, repeated element.

  294. Wessel, David (1979). Timbre Space as a Musical Control Structure. Computer Music Journal 3(2), pp. 45–52; reprinted in Roads & Strawn (1985).

  295. Weyde, Tillman (2004). The Influence of Pitch on Melodic Segmentation. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 128–131.

  296. Wiggins, Geraint (2007). Computer-Representation of Music in the Research Environment. In T.T. Crawford & L. Gibson, eds., AHRC ICT Network Music Expert Seminar, Ashworth, Oxford. Describes the CHARME ("CHARM Extended") knowledge-representation system for music.

  297. Wiggins, Geraint, Miranda, Eduardo, Smaill, Alan, & Harris, Mitch (1993). A Framework for the Evaluation of Music Representation Systems. Computer Music Journal 17(3), pp. 31–42. KW: expressive completeness, structural generality, MIDI, score, musical object, declarative vs. procedural, grammar, hierarchy, music programming language, music calculus, object-oriented representation, symbolic vs. subsymbolic representation

  298. Williams, David, & Webster, Peter (2006). Experiencing Music Technology, 3rd ed. Belmont, California: Thomson Higher Education (but NB the cover says "Thomson/Schirmer").

  299. Wolff, Anthony B. (1977 January). Problems of Representation in Musical Computing. Computers and the Humanities 11(1), pp. 3–12.

    300.  

    Section B. Works on IR, Digital Libraries, Bibliographic Searching, Visualization, etc. in General

  300. Aigner, Wolfgang; Miksch, Silvia; Müller, Wolfgang; Schumann, Heidrun; & Tominski, Christian (2007 June). Visualizing time-oriented data—a systematic view. Computers & Graphics 31(3), pp. 401–409.

  301. Belew, Richard K. (2000). Finding Out About: A Cognitive Perspective on Search Engine Technology and the WWW. Cambridge University Press. A good introductory overview on how search engines work; goes into some details about construction, problems, Zipf's Law. All text based, but pretty valuable. [Annotation: Ian ]

  302. Blair, D., & Maron, M.E. (1985, March). An Evaluation of Retrieval Effectiveness for a Full-text Document-Retrieval System. Communications of the ACM 28(3), pp. 289–299. KW: text IR, recall, large database, vocabulary mismatch, STAIRS. Years ago, this paper attracted considerable attention among text-IR researchers, and it's still of great interest in two very different ways. First, it describes a well-thought-out and meticulously carried out large-scale study of an early full-text IR system, IBM's STAIRS. Of course STAIRS is obsolete, but the methodology they used is still exemplary, and some of the discussion is extremely thought-provoking. On the other hand, the authors reach absurdly negative conclusions about the usefulness of content-based retrieval of text because they made several assumptions that were plausible at the time but really weren't justified, and, as a result, generalized far too much.

  303. Blair, D. (1996). STAIRS Redux: Thoughts on the STAIRS evaluation, ten years after. Journal of the American Society for Information Science 47, pp. 4–22.

  304. Borgman, Christine L. (1986). Why are Online Catalogs Hard to Use? Lessons learned from information retrieval studies. Journal of the American Society for Information Science 37(6), pp. 387–400.

  305. Borgman, Christine L. (1996). Why are Online Catalogs Still Hard to Use? Journal of the American Society for Information Science 47(7), pp. 493–503.

  306. Borgman, Christine L. (2000). From Gutenberg to the Global Information Infrastructure: Access to Information in the Networked World. Cambridge, Mass.: MIT Press.

  307. Bush, Vannevar (1945, July). As We May Think. Atlantic Monthly. In an early vision of a system for accessing huge amounts of information electronically, Bush argues for the practicality of creating a device he called the "memex", complete with hypertext, speech recognition, etc.

  308. Brin, Sergey, and Page, Larry (1998). The Anatomy of a Large-Scale Hypertextual Web Search Engine. Proceedings of Seventh International World-Wide Web Conference (WWW 1998), Brisbane, Australia. Retrieved May 20, 2010 from the World Wide Web: dbpubs.stanford.edu/pub/1998-8 . The classic paper by Google's founders. "In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/ To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago..."

  309. Byrd, Donald (1999). A Scrollbar-based Visualization for Document Navigation. In Proceedings of ACM Digital Libraries 99, pp. 122–129. Retrieved December 20, 2009 from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/DocViewer-ScrollbarPaper.HTML . Describes the "scrollbar with confetti", a visualization of whatever features are of interest in a document that replaces the usual neutral background in a scrollbar. Thus, it gives an overview of the document contents that is automatically coordinated with what's currently in view, in very little screen space -- typically none, since most windows have scrollbars anyway.

  310. Byrd, Donald, & Podorozhny, Rodion (2000). Adding Boolean-quality control to best-match searching via an improved user interface (Technical Report IR-210). Amherst: University of Massachusetts, Computer Science Dept.

  311. Card, Stuart K.; Mackinlay, Jock D.; & Shneiderman, Ben (1999). Readings in Information Visualization: Using Vision to Think. San Francisco: Morgan Kaufmann.

  312. Church, Kenneth (1995). One Term or Two? In Proceedings of ACM SIGIR 1995 Conference on Research and Development in Information Retrieval, pp. 310–318.

  313. Cilibrasi, Rudi & Vitanyi, Paul M. B. (2005). Clustering by Compression. IEEE Transactions on Information Theory 51, no. 4, pp. 1523–1545. "We present a new method for clustering based on compression. The method doesn't use subject-specific features or background knowledge, and works as follows: First, we determine a parameter-free, universal, similarity distance, the normalized compression distance or NCD, computed from the lengths of compressed data files (singly and in pairwise concatenation). Second, we apply a hierarchical clustering method. The NCD is not restricted to a specific application area, and works across application area boundaries... To substantiate our claims of universality and robustness, we report evidence of successful application in areas as diverse as genomics, virology, languages, literature, music, handwritten digits, astronomy, and combinations of objects from completely different domains, using statistical, dictionary, and block sorting compressors." [authors' abstract]

  314. Cleverdon, Cyril (1967). The Cranfield Tests on Index Language Devices. In Sparck Jones & Willett (1997), pp. 47–60.

  315. Davis, Randall; Shrobe, Howard; & Szolovits, Peter (1993). What is a Knowledge Representation? AI Magazine, 14(1), pp. 17–33. Retrieved December 20, 2010, from the World Wide Web: http://medg.lcs.mit.edu/ftp/psz/k-rep.html

  316. Faloutsos, Christos, & Oard, Douglas (1994). A Survey of Information Retrieval and Filtering Methods. Retrieved December 3, 2002, from the World Wide Web: http://www.enee.umd.edu/medlab/filter/papers/survey.ps

  317. Hickey, Thomas B., O'Neill, Edward T., & Toves, Jenny (2002). Experiments with the IFLA Functional Requirements for Bibliographic Records (FRBR). D-Lib Magazine 8(9); retrieved July 10, 2009 from the World Wide Web: http://www.dlib.org/dlib/september02/hickey/09hickey.html.

  318. Hoos, Holger, & Stützle, Thomas (2004). Stochastic Local Search: Foundations and Applications. San Francisco: Morgan Kaufmann.

  319. IFLA Study Group on the Functional Requirements for Bibliographic Records (1998). Functional Requirements for Bibliographic Records - Final Report. Retrieved May 20, 2007 from the World Wide Web: http://www.ifla.org/VII/s13/frbr/frbr.htm.

  320. Information Seeking Support Systems (2009). Information Seeking Support Systems: An Invitational Workshop Sponsored by the National Science Foundation, June 26-27, 2008. Retrieved December 20, 2009 from the World Wide Web: http://ils.unc.edu/ISSS/.

  321. Inselberg, Alfred (1997). Multidimensional Detective. In Card, Mackinlay, & Shneiderman (1999), pp. 107–114.

  322. Joint Steering Committee for Revision of AACR (2002). Anglo-American Cataloguing Rules (2nd ed., 2002 revision). Ottawa: Canadian Library Association; London: Chartered Institute of Library and Information Professionals; Chicago: American Library Association.

  323. Kochumman, Rajiv; Monroy, Carlos; Deng, Jie; Furuta, Richard; & Urbina, Eduardo (2004). Tools for a New Generation of Scholarly Edition Unified by a TEI-based Interchange Format. Proceedings of Joint Conference on Digital Libraries (JCDL 2004), Tucson, Arizona, pp. 368–369. Discusses work on an Electronic Variorum Edition of Cervantes' Don Quixote, including development of MVED, a standalone multisource editor (for use by scholars) and VERI, a web-based "virtual edition" viewer (for the ordinary reader).

  324. Lamping, John & Rao, Ramana (1995). The Hyperbolic Browser: A Focus + Context Technique for Visualizing Large Heirarchies. In Card, Mackinlay, & Shneiderman (1999), pp. 382–408.

  325. Leung, Y.K., & Apperley, M.D. (1994). A Review and Taxonomy of Distortion-Orientation Presentation Techniques. In Card, Mackinlay, & Shneiderman (1999), pp. 350–367.

  326. Lesk, Michael (1997). Practical Digital Libraries: Books, Bytes, and Bucks. San Francisco: Morgan Kaufmann. KW: Memex, text access, images, multimedia, representation, network, security, preservation, human-computer interaction (HCI), intellectual property rights (IPR)

  327. Lesk, Michael (2005). Understanding Digital Libraries, 2nd ed. San Francisco: Morgan Kaufmann.

  328. Library of Congress (2007). Digital Preservation. Retrieved April 10, 2007 from the World Wide Web: http://www.digitalpreservation.gov/

  329. Marchionini, Gary (2006). Toward Human-Computer Information Retrieval. ASIST Bulletin, June/July 2006. Retrieved February 10, 2009 from the World Wide Web: http://www.asis.org/Bulletin/Jun-06/marchionini.html

  330. Mouat, Adrian (2002). XML Diff and Patch Utilities. CS4 dissertation, Heriot-Watt University (Edinburgh, Scotland).

  331. Müller, Meinard; Goto, Masataka Goto; & Schedl, Markus. Multimodal Music Processing. Dagstuhl Follow-Ups, Vol. 3. Retrieved June 20, 2012 from the World Wide Web: http://www.dagstuhl.de/dagpub/978-3-939897-37-8.

  332. Myers, Eugene (1986). An O(ND) Difference Algorithm and its Variations. Algorithmica 1, no.2, pp. 251–266.

  333. North, C., Shneiderman, B., & Plaisant, C. (1996). User Controlled Overviews of an Image Library: A Case Study of the Visible Human. Proceedings of Digital Libraries ’96 Conference. New York: Association for Computing Machinery.

  334. Pickens, Jeremy; Golovchinsky, Gene; Shah, Chirag; Qvarfordt, Pernilla; & Back, Maribeth (2008). Algorithmic mediation for collaborative exploratory search. Proceedings of ACM SIGIR 2008 Conference on Research and Development in Information Retrieval, pp. 315–322. New York: Association for Computing Machinery.

  335. Pierce, John R. (1980). An Introduction to Information Theory, 2nd ed. New York: Dover. A classic! Pierce was at Bell labs when Shannon cooked up the whole field of how information gets transmitted and used. This was probably an advanced text when it was first published (in 1961) but now it reads like a great introduction, with chapters about the role of noise in data, encoding, information theory and art, psychology, some sound information too. All the problems he discusses are still the same ones we have today. [Annotation: Ian Knopke]

  336. Plaisant, Catherine; Milash, Brett; Rose, Anne; Widoff, Seth; & Shneiderman, Ben (1996). LifeLines: Visualizing Personal Histories. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 221ff. Reprinted in Card, Mackinlay, & Shneiderman (1999), pp. 287–294.

  337. Ponte, Jay, & Croft, W. Bruce (1996). Useg: A Retargetable Word Segmentation Procedure for Information Retrieval. (Technical Report IR-75). Amherst: University of Massachusetts, Computer Science Dept.

  338. Shneiderman, Ben (1994). Dynamic Queries for Visual Information Seeking. IEEE Software 11(6), pp. 70–77. Reprinted in Card, Mackinlay, & Shneiderman (1999), pp. 236–243.

  339. Shneiderman, Ben (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings of the IEEE Symposium on Visual Languages, 1996, Boulder, Colorado, pp. 336–343. A seminal paper on information visualization for search.

  340. Shneiderman, Ben (2002). Inventing Discovery Tools: Combining Information Visualization with Data Mining. Information Visualization 1(1), pp. 5–12. ACM Press.

  341. Shneiderman, Ben; Byrd, Donald; & Croft, W. Bruce (1997, January). Clarifying Search: A User-Interface Framework for Text Searches. D-Lib Magazine, January 1997. Retrieved June 10, 2009 from the World Wide Web: http://www.dlib.org/dlib/january97/retrieval/01shneiderman.html.

  342. Shneiderman, Ben; Byrd, Donald; & Croft, W. Bruce (1998, April). Sorting out Searching: A User-Interface Framework for Text Searches. Communications of the ACM 41(4). This is essentially a condensed version of "Clarifying Search", with minor updates.

  343. Smiraglia, Richard P. (2001). Nature of a Work: Implications for the Organization of Knowledge. Lanham, MD: Scarecrow Press.

  344. Sparck Jones, K. & Willett, P., eds. (1997). Readings in Information Retrieval. San Francisco: Morgan Kaufmann.

  345. Swanson, Don R. (1988). Historical Note: Information Retrieval and the Future of an Illusion. Journal of the American Society for Information Science, 39(2), pp. 92–98; in Sparck Jones & Willett (1997), pp. 555–561. An exceptionally thought-provoking commentary on the inherent difficulty of information retrieval. Much of it relates to the difficulty of evaluating relevance, as shown, for example, by the lack of co-citation in scientific literature of certain papers in different fields that, taken together, suggest important conclusions that neither alone could lead to.

  346. Text REtrieval Conference (TREC) (2009). Retrieved February 20, 2013 from the World Wide Web: http://trec.nist.gov

  347. Tillett, Barbara (2004). What is FRBR?: A Conceptual Model for the Bibliographic Universe. Retrieved April 10, 2007 from the World Wide Web: http://www.loc.gov/cds/FRBR.html

  348. Vellucci, Sherry (1997). Bibliographic Relationships in Music Catalogs. Lanham, MD: Scarecrow Press.

  349. Vellucci, Sherry (1998). Bibliographic Relationships. In Jean Weihs, ed., The Principles and Future of AACR: Proceedings of the International Conference on the Principles and Future Development of AACR, Toronto, Ontario, Canada, October 23/25, 1997. Ottawa: Canadian Library Association; London: Library Association Publishing; Chicago: American Library Association. Retrieved May 20, 2009, from the World Wide Web: http://epe.lac-bac.gc.ca/003/008/099/003008-disclaimer.html?orig=/100/200/300/jsc_aacr/bib_rel/r-bibrel.pdf

  350. Voorhees, Ellen (2000). The TREC Conferences: An Introduction. Retrieved June 30, 2004, from the World Wide Web: http://trec.nist.gov/presentations/TREC9/intro/sld001.htm

  351. Wiseman, N., Rusbridge, C., & Griffin, S. (1999, June). The Joint NSF/JISC International Digital Libraries Initiative. D-Lib Magazine 5(6). Retrieved August 23, 2004, from the World Wide Web: http://www.dlib.org/dlib/june99/06wiseman.html

  352. Witten, I., Moffat, A., & Bell, T. (1999). Managing Gigabytes (2nd ed.). San Francisco: Morgan Kaufmann. A thorough and technical but nonetheless highly readable work on information retrieval in general, primarily of text, but with a nod to music and other media.

  353. Yu, Chen; Zhong, Yiwen; Smith, Thomas; Park, Ikhyun; & Huang, Weixia (2008). Visual Data Mining of Multimedia Data. In Proceedings of IEEE Symposium on Visual Analytics Science and Technology (VAST 2008).

    354.  

    Section C. Works on Other Aspects of Music and Music Notation

  354. AKoff Sound Labs (2001). What is Music Recognition?; WAV and MIDI Formats. Retrieved January 20, 2006, from the World Wide Web: http://www.akoff.com/about.html . KW: audio, polyphonic, AMR, WAV, MIDI, accuracy

  355. AMNS (2009). Nightingale. Retrieved April 20, 2009, from the World Wide Web: http://www.ngale.com . KW: CMN, music editing, software

  356. Apel, Willi (1972). Harvard Dictionary of Music, 2nd ed. Cambridge, Mass.: Harvard University Press.

  357. Arnold, Denis, ed. (1983). The New Oxford Companion to Music. 2 vols. Oxford: Oxford University Press.

  358. Backus, John (1977). The Acoustical Foundations of Music, 2nd ed. New York: W. W. Norton. An exceptionally clearly-written book, and one that speaks with authority, since its author was a professor of physics. He was also well aware of the difference between physical and perceptual phenomena, and enough of a musician to avoid the pitfalls hard scientists writing about music often fall into. Of course, it's well behind current knowledge, but, as far a I know, current thinking on the relatively basic matters he covers is largely unchanged. Systematically though briefly covers the major families of instruments.

  359. Bainbridge, David (1997). Extensible Optical Music Recognition. PhD thesis, University of Canterbury, New Zealand. KW: OMR.

  360. Bainbridge, David, & Bell, Tim (2001). The Challenge of Optical Music Recognition. Computers and the Humanities 35(2), pp. 95–121. KW: OMR, musical data acquisition, document image analysis, pattern recognition. The best introduction to the essential problems of OMR I know of. It includes a brief historical survey of attempts to solve them, well-written and with well-chosen figures and examples. As the paper points out, one of the most serious problems of OMR is evaluating it, i.e., finding a way to say how well any system works, either in absolute terms or as compared to any other system.

  361. Bainbridge, David & Bell, Tim (2006). Identifying Music Documents in a Collection of Images. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 47–52. KW: OMR.

  362. Bainbridge, David, & Carter, Nicholas (1997). Automatic Recognition of Music Notation. In Handbook of Optical Character Recognition and Document Image Analysis, H. Bunke and P. Wang (eds). World Scientific, Singapore, 1997, pp. 557–603. KW: OMR.

  363. Barrett, G. Douglas; Winter, Michael; Wulfson, Harris (2007). Automatic Notation Generators. In Proceedings of the 2007 International Computer Music Conference (ICMC 2007), pp. I-25–30.

  364. Battey, Bret (2005). Bezier Spline Modeling of Pitch-Continuous Melodic Expression and Ornamentation. Computer Music Journal 28(4), pp. 25–39.

  365. Belkin, Alan (2006). On Musical Ideas. Retrieved March 30, 2008, from the World Wide Web: www.musique.umontreal.ca/personnel/Belkin/M.ID/M.ID.htm

  366. Bellini, Pierfrancesco, Bruno, Ivan, & Nesi, Paolo (2007). Assessing Optical Music Recognition Tools. Computer Music Journal 31(1), pp. 68–93. KW: OMR, evaluation. OMR evaluation has turned out to be an extremely difficult problem as well as an important one; unfortunately, its difficulty and importance are still not at all well-known. This paper attempts to reach meaningful conclusions by distinguishing between basic symbols (graphic elements: noteheads, flags, the letter "p", etc.) and composite or complete symbols (items with semantics: notes with their associated graphic elements, dynamic marks like "p", "pp", and "mp", etc.), and using results of a survey of experts to assign weights to different errors. A significant contribution to the literature on the subject.

  367. Bellini, Pierfrancesco, Bruno, Ivan, & Nesi, Paolo (2005). An Off-Line Music Sheet Recognition. In George (2005), pp. 40-77. KW: OMR, evaluation, segmentation.

  368. Bellini, Pierfrancesco, & Nesi, Paolo (2004). Automatic justification and line-breaking of music sheets. International Journal of Human-Computer Studies 61(1), July 2004, pp. 104-137. Retrieved June 13, 2004, from the World Wide Web: http://www.sciencedirect.com/science/article/B6WGR-4BRSDTH-1/2/ad50ddc68cd46459fcec0c85f86d76e2

  369. Benward, Bruce; Jackson, Barbara Garvey; & Jackson, Bruce R. (2000). Practical Beginning Theory: A Fundamentals Worktext. 8th ed. Boston: McGraw-Hill, c2000. A popular textbook on elementary music theory.

  370. Bernstein, Leonard (1976). The Unanswered Question: Six Talks at Harvard. Harvard University Press. This book is a well-edited transcription of the "The Charles Eliot Norton Lectures, 1973". It involves to a great extent analogies between music and language, influenced (as Bernstein makes clear) by his discovery in the early 1970's of the work of Noam Chomsky.

  371. Bosanquet, R. H. M. (1874). The Theory of the Division of the Octave, and the Practical Treatment of the Musical Systems Thus Obtained. Revised Version of a Paper Entitled 'On Just Intonation in Music; with a Description of a New Instrument for the Easy Control of Systems of Tuning other than the Equal Temperament of 12 Divisions in the Octave...' Proceedings of the Royal Society of London , vol. 23 (1874-75), pp. 390-408. Retrieved Oct. 15, 2007, from the World Wide Web: http://www.journals.royalsoc.ac.uk/content/t475165761130574/fulltext.pdf

  372. Bugge, Esben Paul; Juncher, Kim Lundsteen; Mathiasen, Brian Søborg; & Simonsen, Jakob Grue (2011). Using Sequence Alignment and Voting to Improve Optical Music Recognition from Multiple Recognizers. In Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), pp. 405–410. KW: OMR.

  373. Burkhart, Charles (1994). Anthology for Music Analysis, 5th ed. Wadsworth Publishing Company.

  374. Burkholder, J. Peter (1995). All Made of Tunes: Charles Ives and the Uses of Musical Borrowing. New Haven: Yale University Press.

  375. Burkholder, J. Peter (2005). Norton Anthology of Western Music, 5th ed. 2 vols. W.W. Norton.

  376. Burkholder, J. Peter (2006). Norton Recorded Anthology of Western Music. 2 vols. W.W. Norton.

  377. Burkholder, J. Peter; Grout, Donald J.; & Palisca, Claude (2005). A History of Western Music, 7th ed. W.W. Norton.

  378. Byrd, Donald (1984). Music Notation by Computer (doctoral dissertation, Computer Science Dept., Indiana University). Ann Arbor, Michigan: UMI ProQuest (order no. 8506091); also available from www.npcimaging.com. Retrieved (in scanned form) February 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/Papers/DonDissScanned.pdf . KW: CMN, music formatting, artificial intelligence, counterexample, FAHQMN, notation

  379. Byrd, Donald, & Schindele, Megan (2007). Prospects for Improving Optical Music Recognition with Multiple Recognizers. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 41–46; revised and expanded version retrieved February 20, 2013, from the World Wide Web: http://www.informatics.indiana.edu/donbyrd/MROMRPap . KW: OMR, classifier, recognizer, evaluation

  380. Byrd, Donald, Guerin, William, Schindele, Megan, & Knopke, Ian (2010). OMR Evaluation and Prospects for Improved OMR via Multiple Recognizers. Retrieved February 20, 2013, from the World Wide Web: MROMR2010Pap/OMREvaluation+Prospects4MROMR.doc. KW: OMR.

  381. Cano, Pedro; Loscos, Alex; Bonada, Jordi;De Boer, Maarten; & Serra, Xavier (2000). Voice Morphing System for Impersonating in Karaoke Applications. In Proceedings of the 2000 International Computer Music Conference (ICMC 2000).

  382. Carter, Nicholas (1989). Automatic Recognition of Printed Music in The Context Of Electronic Publishing (doctoral dissertation, Depts. of Physics and Music, University of Surrey). Retrieved May 10, 2005, from the World Wide Web: http://www.npcimaging.com/thesis/thesis.html . KW: OMR.

  383. Choudhury, G. Sayeed, Droettboom, M., DiLauro, T., Fujinaga, I., & Harrington, B. (2000). Optical Music Recognition System within a Large-Scale Digitization Project. Read at the First International Symposium on Music Information Retrieval (ISMIR 2000); retrieved November 6, 2002, from the World Wide Web: http://ciir.cs.umass.edu/music2000

  384. Choudhury, G. Sayeed, C. Requardt, I. Fujinaga, T. DiLauro, E. W. Brown, J. W. Warner, & B. Harrington (2004). Digital workflow management: The Lester S. Levy digitized collection of sheet music. Retrieved December 1, 2004, from the World Wide Web: http://firstmonday.org/issues/issue5_6/choudhury/index.html

  385. Choudhury, G. Sayeed, DiLauro, Tim, Droettboom, Michael, Fujinaga, Ichiro, & MacMillan, Karl (2001, February). Strike Up the Score: Deriving Searchable and Playable Digital Formats from Sheet Music. D-Lib Magazine 7(2). Retrieved February 16, 2004, from the World Wide Web: http://www.dlib.org

  386. Clough, John, Conley, Joyce, & Boge, Claire (1999). Scales, Intervals, Keys, Triads, Rhythm, and Meter, 3rd ed. New York: W. W. Norton & Company. Covers the basics of music theory.

  387. Cope, David, et al (2001). Virtual Music. "With commentary by Douglas Hofstadter, and with perspectives and analysis by Eleanor Selfridge-Field, Bernard Greenberg, Steve Larson, Jonathan Berger, and Daniel Dennett." Includes a CD. Cambridge, Mass.: MIT Press. Cope has written extensively about his remarkable composing program EMI (Experiments in Musical Intelligence), which "learns" a musical style -- normally that of a specific composer -- by analyzing a body of music, and then churns out surprisingly interesting and convincing new music in that style. This book, incorporating contributions by a group of distinguished experts on various aspects of what EMI does, offers a good perspective.

  388. Cunningham, Stuart; Gebert, Nicole; Picking, Rich, & Grout, Vic (2006). Web-Based Music Notation Editing. In Proceedings of IADIS - International Conference on WWW/Internet, Murcia, Spain.

  389. Dalitz, Christoph, & Karsten, Thomas (2005). Using the Gamera Framework for Building a Lute Tablature Recognition System. In Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, England, pp. 478–481. KW: OMR.

  390. Dalitz, Christoph; Droettboom, Michael; Czerwinski, Bastain; & Fujinaga, Ichiro (2008, May). A Comparative Study of Staff Removal Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(5), pp. 753-766. Retrieved March 21, 2008, from the World Wide Web: http://lionel.kr.hs-niederrhein.de/~dalitz/data/publications/index-en.html . KW: OMR.

  391. Davis, Elizabeth, coordinating ed. (1997). A Basic Music Library: Essential Scores and Sound Recordings, 3rd ed. Chicago: American Library Association. "Compiled by the Music Library Association." Lists 7,000 recordings and 3,000 printed scores coded for different levels of collecting. [Annotation: Google Books]

  392. Donington, Robert (1982). Baroque Music: Style and Performance, a Handbook. New York: W. W. Norton & Company. Describes how Baroque music was performed and appreciated by its contemporaries and suggests choices of tempo, rhythm, ornament, and accompaniment for modern performances. [Annotation: Google Books]

  393. Droettboom, Michael, & Fujinaga, Ichiro (2004). Micro-level groundtruthing environment for OMR. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 497–500. KW: OMR.

  394. Forney, Kristine (2003). The Norton Scores: A Study Anthology, 9th ed. 2 vols. W.W. Norton.

  395. Fritts, Lawrence. The University of Iowa Musical Instrument Samples. Retrieved August 10, 2007, from the World Wide Web: http://theremin.music.uiowa.edu/MIS.html

  396. Fujinaga, Ichiro (1997). Adaptive optical music recognition. Doctoral dissertation, McGill University. KW: OMR, k-NN classifier, genetic algorithm.

  397. Fujinaga, Ichiro (2004). Application of Optical Music Recognition technologies for the development of OCVE. Technical report. Retrieved May 10, 2007, from the World Wide Web: http://www.ocve.org.uk/content/reports/index.html . KW: OMR.

  398. Fujinaga, Ichiro (2005). Staff Detection and Removal. In George (2005), pp. 1-39. KW: OMR, image processing, projection, run-length coding, connected-component analysis

  399. Fujinaga, Ichiro, & Riley, Jenn (2002). Digital Image Capture of Musical Scores. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp. 261–262. KW: OMR; resolution; best practice.

  400. Gardner, Martin (1978, April). Mathematical Games: White and brown music, fractal curves and one-over-f fluctations. Scientific American, pp. 16ff. A fascinating discussion of the then-recent discovery by Voss and Clarke that the spectral density of fluctuations in the audio power and frequencies of many musical selections vary approximately as 1/f, and that sequences of random notes generated with such probabilities sound pleasing, while sequences generated by 1/f^2 noise (equivalent to Brownian motion) sound too random, or by white noise (1/f^0 = 1)

  401. George, Susan, ed. (2005). Pen-based Input for On-line Handwritten Music Notation. In George (2005), pp. 128-60. One of the few papers on recognition of handwritten music notation, especially online. An interesting feature is its comparison of neural-net algorithms, including one with a system of voting among networks.

  402. George, Susan, ed. (2005). Visual Perception of Music Notation: On-Line and Off-Line Recognition. Hershey, PA: IRM Press. A collection of papers by the editor and others, some very good, some less good and/or poorly edited. Much of the book is about on-line OMR, where the computer can "watch" a user drawing the music, and the problems involved are quite different from those of the usual off-line situation.

  403. Gould, Elaine (2011). Behind Bars. London: Faber Music. A textbook on music notation. Comprehensive and authoritative, it's showing signs of becoming the standard text.

  404. Gurevich, Michael (2006). JamSpace: A Networked Real-time Collaborative Music Environment. CHI Extended Abstracts 2006, pp. 821–826.

  405. Hall, Gary (2004, October). Colors of the Rainbow: A By-the-Book Look at CD Standards and Formats. Electronic Musician 20(12), pp. 74–80.

  406. Hall, Gary (2004, November). Optical Media Wars: DVD vs. SACD. Electronic Musician 20(13), pp. 66–73.

  407. Hindemith, Paul, translated by Arthur Mendel (1945). Craft of Musical Composition, Book I: Theory, 4th ed. New York: Associated Music Publishers.

  408. Hook, Julian (2007, July). Enharmonic Systems: A Theory of Key Signatures, Enharmonic Equivalence, and Diatonicism. Journal of Mathematics and Music, 1(2), pp. 99-120.

  409. Hook, Julian (2011 December). How to Perform Impossible Rhythms. Music Theory Online 17, no. 4.

  410. Indiana University Center for Electronic and Computer Music (2008). Retrieved February 20, 2008, from the World Wide Web: http://www.indiana.edu/~emusic/

  411. Interactive MusicNetwork (2004). OMR Bibliography, v.2 (28 Jan 2004). Retrieved May 13, 2005, from the World Wide Web: http://www.interactivemusicnetwork.org/wg_imaging/upload/omrbib-20040128e.htm

  412. Ishkur (2006). Ishkur's Guide to Electronic Music. Retrieved December 30, 2006, from the World Wide Web: http://www.di.fm/edmguide/edmguide.html . An amazing guide to "electronic music" in a broad sense, obviously by someone with a non-art-tradition perspective, though it displays reasonable familiarity with musique concrete and the electroacoustic works of Varese, Stockhausen, etc. Has an amusing and informative tutorial on the history of electronic music. An outstanding feature is the presence of hundreds -- perhaps thousands -- of audio examples.

  413. Keller, Robert M.; Jones, Stephen; Morrison, David; Thom, Belinda; & Wolin, Aaron (2006). A Computational Framework Enhancing Jazz Creativity. Third Workshop on Computational Creativity, European Conference on Artificial Intelligence. Retrieved August 14, 2007, from the World Wide Web: http://www.cs.hmc.edu/~keller/jazz/improvisor/jazzCreativity.pdf

  414. Kilian, Jürgen, & Hoos, Holger (2002). Voice Separation — A Local Optimization Approach. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp. 39–46.

  415. Kostka, Stefan; & Payne, Dorothy (2003). Tonal Harmony: With An Introduction To Twentieth-Century Music, 5th ed. McGraw-Hill. A popular music theory textbook.

  416. Kunkel, Nathaniel (2009, March). Now That We Can Do Anything, What Are You Going To Do? Electronic Musician 25(3), p. 74. In one page, Kunkel makes thought-provoking comments on more than one significant issue of music technology. Superb; worth reading more than once.

  417. Lamkin, Linda L. (2005). An Examination of Correlations between Flutists' Linguistic Practices and Flute Sound Production. In Proceedings of the 2005 Conference on Interdisciplinary Musicology (CIM05), Montréal, Québec.

  418. Lansky, Paul (2004). The Importance of Being Digital. Retrieved November 20, 2006, from the World Wide Web: http://silvertone.princeton.edu/~paul/lansky_beingdigital.htm

  419. Larson, Steve (2004, Summer). Musical Forces and Melodic Expectations: Comparing Computer Models and Experimental Results. Music Perception 21(4), pp. 457–499.

  420. Lobb, Richard, Bell, Tim, & Bainbridge, David (2005). Fast Capture of Sheet Music for an Agile Digital Music Library. In Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, pp. 145–152.

  421. Loy, Gareth (2006). Musimathics: The Mathematical Foundations of Music. Volume I: Musical Elements. MIT Press. "Mathematics can be as effortless as humming a tune, if you know the tune," writes Gareth Loy. In Musimathics, Loy teaches us the tune, providing a friendly and spirited tour of the mathematics of music -- a commonsense, self-contained introduction for the nonspecialist reader. It is designed for musicians who find their art increasingly mediated by technology, and for anyone who is interested in the intersection of art and science. --from the publisher's Web site

  422. Loy, Gareth (2007). Musimathics: The Mathematical Foundations of Music. Volume II: Musical Signals. MIT Press.

  423. MacMillan, Karl, Droettboom, Michael, & Fujinaga, Ichiro (2002). Gamera: Optical music recognition in a new shell. In Proceedings of the International Computer Music Conference, pp. 482–485. KW: OMR.

  424. Maxwell III, John Turner (1981). Mockingbird: An Interactive Composer's Aid. B.S. and M.S. thesis, MIT. Describes in detail the author’s seminal research (in collaboration with Severo Ornstein) in interactive music-notation editing. Their work is not very well-known -- they used an experimental computer, operating system, and programming language, none of which ever became available to the public -- but it has been tremendously influential nonetheless.

  425. Maxwell III, John Turner, & Ornstein, Severo M. (1983). Mockingbird: A Composer’s Amanuensis. Technical report, Xerox Palo Alto Research Center. An overview of the authors’ work described in more detail in Maxwell's thesis (q.v.).

  426. Maxwell III, John Turner, & Ornstein, Severo M. (1984). Mockingbird: A Composer’s Amanuensis. Byte 9(1). An overview of the authors’ work described in more detail in Maxwell's thesis (q.v.).

  427. Maxwell III, John Turner, & Ornstein, Severo M. (1984). DigiBarn TV: Video on the Mockingbird screen-based music scoring system. The webpage says: "Mockingbird was the first screen-based computer music scoring system. It was built at Xerox PARC in 1980 by Severo M. Ornstein and John T. Maxwell. It's purpose was to explore the assistance that computers might provide to composers, especially those who utilized a piano keyboard in the process of composition..." Retrieved July 10, 2008, from the World Wide Web: www.digibarn.com/collections/movies/digibarn-tv/gui-movies/xerox/mockingbird/index.html

  428. McPherson, John (2002). Introducing Feedback into an Optical Music Recognition System. In Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp. 259–260. KW: OMR. Nearly all OMR systems I'm aware of operate in a rigidly bottom-up fashion that (in my opinion) has no hope of doing a good job with notationally complex music. The system described in this paper is, to my knowledge, the first to take a more flexible and promising approach.

  429. Miller, Dennis (2002, July). Csound Comes of Age. Electronic Musician 18(8), pp. 38–49.

  430. Miller, Dennis (2008, October). Going with the Grain: Ten Granular Synthesis Programs to Slice and Dice Your Sounds. Electronic Musician 24(10), pp. 50–62.

  431. Miller, Michael (2002). The Complete Idiot's Guide to Music Theory. Alpha Books.

  432. Miranda, Eduardo, & Brouse, Andrew (2005). Toward Direct Brain-Computer Musical Interfaces. In Proceedings of the 2005 International Conference on New Interfaces for Musical Expression (NIME05), Vancouver, BC, Canada, pp. 216–219.

  433. Mohrlok, Werner (2003). The Hermode Tuning System. Retrieved October 30, 2007, from the World Wide Web: eceserv0.ece.wisc.edu/~sethares/paperspdf/hermode.pdf

  434. Monelle, Raymond (1992). Linguistics and Semiotics in Music. Harwood Academic Publishers.

  435. Ng, Kia C. (2005). Optical Music Analysis for Printed Music Score and Handwritten Music Manuscript. In George (2005), pp. 108-127. KW: OMR, reconstruction.

  436. Ng, Kia C., & Jones, A. (2003). A Quick-Test for Optical Music Recognition Systems. 2nd MUSICNETWORK Open Workshop, Workshop on Optical Music Recognition System, Leeds, September 2003. KW: OMR, evaluation.

  437. Ng, Kia C.; Barthelmy, Jerome; Ong, Bee; Bruno, Ivan; & Nesi, Paolo (2005). CIMS: Coding Images of Music Sheets, version 3.4. Interactive MusicNetwork working paper. Available at www.interactivemusicnetwork.org/documenti/view_document.php?file_id=1194. KW: OMR, music imaging, music digitization, sheet music, image processing, scanner, optical music restoration. Despite the confusing title, this is a general report on OMR and related technologies, with an interesting discussion of OMR evaluation and an extensive bibliography.

  438. Pierce, John R. (1992). The Science of Musical Sound, Revised Edition. New York: W. H. Freeman. A fascinating, relatively non-technical exploration of musical acoustics and psychoacoustics, with considerable attention in its mere 250 or so pages to electronic music and digital sound synthesis: the first chapter is entitled "Sound, Music, and Computers", and there are brief appendices on MIDI and on MAX. Numerous diagrams and photos enhance both its clarity and interest. Another nice feature is its annotated bibliography.

  439. Porter, Hayden (2004, February). Phone It In! Electronic Musician 20(3), pp. 76–86. KW: ringtone, cell phone, SP-MIDI, polyphony.

  440. Powell, Steven (2002). Music Engraving Today: The Art and Practice of Digital Notesetting. New York: Brichtmark. Discusses how to do music "engraving" with personal computers, especially using Finale and Sibelius.

  441. Pugin, Laurent (2006). Optical Music Recognition of Early Typographic Prints using Hidden Markov Models. In Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, pp. 53–56.

  442. Rastall, Richard (1982). The Notation of Western Music. New York: St. Martin’s Press.

  443. Raphael, Christopher & Wang, Jingya (2011). New Approaches to Optical Music Recognition. In Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), pp. 305–310. KW: OMR. Advocates mixing top-down and bottom-up recognition in a way that promises to avoid both the frequent nonsensical results of the usual bottom-up methods and the inflexibility of typical top-down methods; cf. my comments on McPherson (2002).

  444. Read, Gardner (1969). Music Notation, 2nd ed. Boston: Crescendo. A standard textbook on music notation; despite its pre-computer vintage, still contains a great deal of valuable information.

  445. Read, Gardner (1978). Modern Rhythmic Notation. Bloomington: Indiana University Press.

  446. The Real Vocal Book (n.d.). Title page lists as publisher "Real Vocal Book Press".

  447. Rebelo, Ana; Fujinaga, Ichiro; Paszkiewicz, Filipe; Marcal, Andre R. S.; Guedes, Carlos; & Cardoso, Jaime S. (2012). Optical music recognition: state-of-the-art and open issues. International Journal of Multimedia Information Retrieval (March 2012), pp. 1–18. KW: computer music, image processing, machine learning, music performance. The most recent detailed survey of OMR work and the most recent discussion of open issues in OMR I know of.

  448. Reed, K. Todd (1995). Optical Music Recognition. M. Sc. thesis, Dept. of Computer Science, University of Calgary. KW: OMR.

  449. Risatti, Howard (1975). New Music Vocabulary. Urbana: University of Illinois Press.

  450. Roland, Perry (1997). Proposed Musical Characters in Unicode. In Selfridge-Field (1997), pp. 553–562.

  451. Ross, Ted (1970). The Art of Music Engraving and Processing. Miami: Hansen. This classic work has by far the most detailed information on positioning and spacing of symbols in music notation of any book I know of. It’s somewhat biased towards pop music, but not excessively.

  452. Rossant, Florence, & Bloch, Isabelle (2007). Robust and Adaptive OMR System Including Fuzzy Modeling, Fusion of Musical Rules, and Possible Error Detection. EURASIP Journal on Advances in Signal Processing, vol. 2007, article ID 81541. KW: OMR. Nearly all OMR systems I'm aware of operate in a rigidly bottom-up fashion that (in my opinion) has no hope of doing a good job with notationally complex music. The system described in this paper takes a more promising approach.

  453. Sacks, Oliver (2007). Musicophilia. Alfred A. Knopf.

  454. Sadie, Stanley, ed. (2001). The New Grove Dictionary of Music and Musicians, 2nd ed. Macmillan. The standard, and by far the most detailed, general music reference work in English.

  455. Selfridge-Field, Eleanor, Carter, Nicholas, and others (1994). Optical Recognition: A Survey of Current Work; An Interactive System; Recognition Problems; The Issue of Practicality. In Hewlett, W., & Selfridge-Field, E. (Eds.), Computing in Musicology, vol. 9, pp. 107–166. Menlo Park, California: Center for Computer-Assisted Research in the Humanities (CCARH). KW: OMR. Important, pioneering work, incorporating the first and still one of the very few serious attempts to evaluate the performance of existing OMR systems. Includes an annotated bibliography.

  456. Sheridan, Scott, & George, Susan (2004). Defacing Music Scores for Improved Recognition. In Proceedings of the 2nd Australian Undergraduate Students' Computing Conference. KW: OMR, staff removal.

  457. Stefik, Andreas; Stefik, Melissa; & Curtiss, Mark (2008). An Automatic Translator for Semantically Encoded Musical Languages. Computer Music Journal 31(4), pp. 33–46.

  458. Stone, Kurt (1980). Music Notation in the Twentieth Century: A Practical Guidebook. New York: W. W. Norton. A well-thought-out and well-organized guide to notation for 20th-century music, incorporating the views of a large number of composers and scholars.

  459. Szwoch, Mariusz (2008). Using MusicXML to Evaluate Accuracy of OMR Systems. In Proceedings of the 5th international Conference on Diagrammatic Representation and Inference, Herrsching, Germany, pp. 419–422. KW: OMR.

  460. Strawn, John (1987). Analysis and Synthesis of Musical Transitions Using the Discrete Short-time Fourier Transform. Journal of the Audio Engineering Society 35(1/2), pp. 3–14. Retrieved July 20, 2008, from the World Wide Web: http://www.s-systems-inc.com/pubs/jaes_transitions.zip

  461. Tomita, Yo (1994). Bach, the Font: Inline Musical Graphics for Databases and Spreadsheets. In Hewlett, W., & Selfridge-Field, E. (Eds.), Computing in Musicology, vol. 9, pp. 61–64. Menlo Park, California: Center for Computer-Assisted Research in the Humanities (CCARH).

  462. Tovey, Donald Francis (1944; reprinted 1956). The Forms of Music. Cleveland: Meridian Books. A collection of essays (originally written as articles for the Encyclopedia Britannica) by one of the most insightful writers on music I know of.

  463. Unicode (2005). Code Charts for Symbols and Punctuation. Retrieved October 10, 2005, from the World Wide Web: http://www.unicode.org/charts/symbols.html . As of the current version (4.1.0), Unicode includes Ancient Greek and Byzantine as well as "Western" musical symbols.

  464. Von Foerster, Heinz, & Beauchamp, James W., eds. (1969). Music by Computers. New York: John Wiley & Sons. Includes chapters by a number of the pioneers on their work in synthesis of interesting and realistic sounds, algorithmic composition, etc., plus supplementary recorded examples (on the technology of the time, small flexible 33-1/3 rpm records).

  465. Warner, Thomas (1977). Tromlitz's Flute Treatise: A Neglected Source of Eighteenth-Century Performance Practice. In A Musical Offering: Essays in Honor of Martin Bernstein, ed. by E. Clinkscale and C. Brook. Pendragon Press.

  466. Weaner, Maxwell; Boelke, Walter; Briodo, Arnold; & Dorff, Daniel (1966; revised 1993). Standard Music Notation Practice. Music Publishers' Association & Music Educators National Conference. Retrieved January 20, 2009, from the World Wide Web: http://mpa.org/music_notation/standard_practice.pdf . A survey of music-notation rules actually used by music publishers. Brief and far from comprehensive, but of much interest nonetheless, with its authoritative origin.

  467. Wilkinson, Scott (2005, May). Hermode Tuning. Electronic Musician 21(5), p. 32.

  468. Worship in Song: A Friends Hymnal (1996). Philadelphia: Friends General Conference. The only relevance of this work to music informatics is that this is one of the sources of statistics used in Byrd & Crawford (2002) and in my "whitepaper" Musical Themes and Occurrences of Melodic Confounds.

  469. Xenakis, Iannis (1963). Musique Formelles; English ed. (1971), Formalized Music. Indiana University Press. An important book by an extraordinary composer: it has justly been called one of the two seminal works on algorithmic composition of its era (the other being Hiller and Isaacson's Experimental Music).

    470.  

    Section D. Miscellaneous Works (not specific to music, IR, bibliographic searching, etc.)

  470. Bar-Hillel, Y. (1960). A Demonstration of the Nonfeasibility of Fully Automatic High-Quality Translation. Appendix III to The Present Status of Automatic Translation of Languages. In Advances in Computers, vol. I (F.L. Alt, ed.), pp. 158–163. Academic Press.

  471. Boyle, James; Jenkins, Jennifer; & Aoki, Keith (2006). Bound By Law? Tales From the Public Domain. Center for the Study of the Public Domain, Duke Law School. Retrieved June 30, 2006, from the World Wide Web: http://www.law.duke.edu/cspd/comics/. Many observers feel that intellectual-property law in the U.S. these days is heavily biased towards the IPR owners and away from the public. Though addressed primarily to documentary filmmakers, this work -- in comic-book format! -- is an excellent introduction to IPR issues for those interested in music, especially since a great many of the examples cited involve music. KW: copyright infringement, Fair Use, IPR, public domain

  472. Churchill, Caryl. (1982). Top Girls. London: Methuen. Byrd & Crawford (2002) cites this play simply as a rare example in text of "polyphony" with explicitly-notated synchronization.

  473. Crews, Kenneth (2005). Copyright Law for Librarians and Educators: Creative Strategies and Practical Solutions. American Library Association. KW: copyright, Fair Use, IPR, public domain

  474. Goodman, Nelson (1976). Languages of Art: An Approach to a Theory of Symbols, 2nd ed. Indianapolis: Hackett Publishing. Discusses, from the viewpoint of a philosopher, such questions as what a notation is and what defines a specific work of art. Quite a bit of the content is specific to music, though, interestingly, he uses the term "score" for many arts.

  475. Hayakawa, S.I., & Hayakawa, Alan R. (1990). Language in Thought and Action, 5th ed. San Diego: Harcourt. The best discussion I've ever seen of generally neglected but vital aspects of communication: for example, (1) the prevalance of thinking in terms of a "two-valued orientation" for complex issues that would become far less difficult if people could accept the possibility of intermediate positions (a "multi-valued orientation"), and (2) the difference between a word's denotations and its connotations. The Hayakawas were thinking of communication between people, but much of what they say applies to human-to-computer communication as well. For example, one way their work applies to music informatics is that the information in music has little if any denotation, but a great deal of connotation.

  476. Gorder, Pam Frost (2008, July/August). Medical Software has Astronomers Seeing Stars. IEEE Computing in Science and Engineering 24(3), pp. 4–9.

  477. Herr, Bruce W.; Huang, Weixia; Penumarthy, Shashikant; & Börner, Katy (2007). Designing Highly Flexible and Usable Cyberinfrastructures for Convergence. In William S. Bainbridge and Mihail C. Roco (Eds.) Progress in Convergence -- Technologies for Human Wellbeing. Annals of the New York Academy of Sciences, Boston, MA, volume 1093, pp. 161–179.

  478. Hofstadter, Douglas (1979; twentieth-anniversary edition, 1999). Gödel, Escher, Bach: An Eternal Golden Braid. New York: Basic Books.

  479. Hutchinson, Ann (1977). Labanotation: The System of Analyzing and Recording Movement, 3rd ed. New York: Theatre Arts Books.

  480. Klopmeyer, Jeff (2008, March). Playing Concerts in Second Life. Electronic Musician 24,3, pp. 39–43.

  481. Norman, Don (1988). The Psychology of Everyday Things. New York: Basic Books. Published in paperback as The Design of Everyday Things. The Amazon.com editorial review says "Anyone who designs anything to be used by humans -- from physical objects to computer programs to conceptual tools -- must read this book, and it is an equally tremendous read for anyone who has to use anything created by another human. It could forever change how you experience and interact with your physical surroundings, open your eyes to the perversity of bad design and the desirability of good design, and raise your expectations about how things should be designed." I agree completely.

  482. Oliver, S.H., & Berkebile, D.H. (1968). The Smithsonian Collection of Automobiles and Motorcycles. Washington: Smithsonian Institution Press. The automobile user interface is something we now take for granted, but it took decades to reach the current level of refinement and standardization, and remaining inconsistencies like left vs. right variations from country to country still cause serious problems for travelers. This book gives some idea of the total lack of consistency, and and in some cases what appears to be a total lack of common sense, in the interfaces of early automobiles.

  483. Pace, David, & Middendorf, Joan, eds. (2004). Decoding the Disciplines: Helping Students Learn Disciplinary Ways of Thinking. New Directions for Teaching and Learning no. 98. San Francisco: Jossey-Bass.

  484. Rapoport, Anatol (1955). Technological Models of the Nervous System. Reprinted in Sayre & Crosson (1963).

  485. Rosenberg, Daniel (2004, Spring). The Trouble with Timelines. Cabinet, issue 13. Retrieved May 20, 2009, from the World Wide Web: http://www.cabinetmagazine.org/issues/13/timelineIntro.php

  486. Rosenberg, Daniel (2007). Joseph Priestley and the Graphic Invention of Modern Time. Studies in Eighteenth Century Culture 36(1), pp. 55–103.

  487. Sayre, Kenneth M., & Crosson, Frederick J. (1963). The Modeling of Mind: Computers and Intelligence. University of Notre Dame Press. Old as it is, I think this anthology is still very worthwhile; it includes classic papers in several areas that are thought-provoking even today. Among them are a lengthy excerpt from Hiller and Isaacson (1959); Rapoport (1955); and John Lucas' famously wrong-headed argument that Goedel's theorem shows "strong" artificial intelligence is impossible (elegantly refuted by C.H. Whitely with the observation that "Lucas cannot consistently assert this statement"!).

  488. Schreibman, Susan; Siemens, Ray; & Unsworth, John, eds. (2004). A Companion to Digital Humanities. Oxford: Blackwell. Retrieved May 20, 2009, from the World Wide Web: http://www. .org/companion/. A standard text on the subject, containing 37 chapters by experts on various subjects. In addition to the one on music, includes chapters on multimedia, performing arts, databases, digital libraries, preservation, etc.

  489. Shneiderman, Ben (1998). Designing the User Interface, 3rd ed. Addison-Wesley.

  490. Strong, William S. (1999). The Copyright Book: A Practical Guide, 5th ed. Cambridge, Mass.: MIT Press. KW: copyright infringement, Fair Use, licensing, permissions, IPR, public domain.

  491. Tufte, Edward (2001). The Visual Display of Quantitative Information, 2nd ed. Cheshire, Connecticut: Graphics Press. An extraordinary book on how to (and how not to) convey technical information visually. Full of interesting examples from real publications.

  492. Tufte, Edward (1990). Envisioning Information. Cheshire, Connecticut: Graphics Press. See comments on his The Visual Display of Quantitative Information.

  493. Tufte, Edward (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, Connecticut: Graphics Press. See comments on his The Visual Display of Quantitative Information. Of particular interest is a lengthy discussion of the tragic decision to launch the space shuttle Challenger, despite a last-minute effort by engineers to convince NASA not to proceed at the low temperature expected. Tufte argues convincingly that their effort failed mostly because the graphics they used buried the vital information -- the correlation between launch temperature and problems with the booster rockets -- in irrelevant details. More directly relevant, the book has chapters entitled "Parallelism: Repetition and Change, Comparison and Surprise" and "Multiples in Space and Time".

 

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Copyright 2005-13, Donald Byrd