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Community

Here are selected publications by MusicXML community authors. Some of the publications have MusicXML as their primary topic, but most describe how MusicXML is being used in applications and research.

In English

2019

• Grachten, M., Cancino-Chacón, C. and Gadermaier, T. partitura: A Python Package for Handling Symbolic Musical Data. Late-Breaking Demo at the 20th International Society for Music Information Retrieval Conference (Delft, The Netherlands, November 4-8, 2019).
• Holzapfel, A. and Benetos, E. Automatic Music Transcription and Ethnomusicology: A User Study. In Proceedings of the 20th International Society for Music Information Retrieval Conference (Delft, The Netherlands, November 4-8, 2019), pp. 678-684.
• Jeong, D. et al. VirtuosoNet: A Hierarchical RNN-Based System for Modeling Expressive Piano Performance. In Proceedings of the 20th International Society for Music Information Retrieval Conference (Delft, The Netherlands, November 4-8, 2019), pp. 908-915.
• Katsiavalos, A., Collins, T. and Battey, B. An Initial Computational Model for Musical Schemata Theory. In Proceedings of the 20th International Society for Music Information Retrieval Conference (Delft, The Netherlands, November 4-8, 2019), pp. 166-172.
• Miller, M. et al. Visual Pattern Analysis Using Digital Sheet Music. Late-Breaking Demo at the 20th International Society for Music Information Retrieval Conference (Delft, The Netherlands, November 4-8, 2019).

2018

• Pulimootil Achankunju, S. Music Search Engine from Noisy OMR Data. In Proceedings of the 1st International Workshop on Reading Music Systems (Paris, September 20, 2018), pp. 23-24.
• Roggenkemper, H. and Roggenkemper, R. How Can Machine Learning Make Optical Music Recognition More Relevant for Practicing Musicians? In Proceedings of the 1st International Workshop on Reading Music Systems (Paris, September 20, 2018), pp. 25-26.
• Das, O., Kaneshiro, B. and Collins, T. Analyzing and Classifying Guitarists from Rock Guitar Solo Tablature. In Proceedings of the 15th Sound and Music Computing Conference (Limassol, Cyprus, July 4-7, 2018), pp. 232-238.
• Hamanaka, M., Hirata, K. and Toto, S. GTTM Database and Manual Time-Span Tree Generation Tool. In Proceedings of the 15th Sound and Music Computing Conference (Limassol, Cyprus, July 4-7, 2018), pp. 462-467.
• Lionello, M. and Ramirez, R. A Machine Learning Approach to Violin Vibrato Modelling in Audio Performances and a Didactic Application for Mobile Devices. In Proceedings of the 15th Sound and Music Computing Conference (Limassol, Cyprus, July 4-7, 2018), pp. 347-353.

2017

• Sun, S. H. and Cuthbert, M. S. Emotion Painting: Lyric, Affect, and Musical Relationships in a Large Lead-Sheet Corpus. In Empirical Musicology Review, 12 (3-4), 2017, pp. 327-348.
• Caro Repetto, R. and Serra, X.  A Collection of Music Scores for Corpus Based Jingju Singing Research. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 46-52.
• Sears, D. R. W. et al. Modeling Harmony with Skip-Grams. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 332-338.
• Cogliati, A. and Duan, Z. A Metric for Music Notation Transcription Accuracy. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 407-413.
• Parada-Cabaleiro, E. et al. The SEILS Dataset: Symbolically Encoded Scores in Modern-Early Notation for Computational Musicology. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 575-581.
• Lim, H., Rhyu, S. and Lee, K. Chord Generation from Symbolic Melody Using BLSTM Networks. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 621-627.
• van der Wel, E. and Ullrich, K. Optical Music Recognition with Convolutional Sequence-to-Sequence Models. In Proceedings of the 18th International Society for Music Information Retrieval Conference (Suzhou, China, October 23-27, 2017), pp. 731-737.
• Herremans, D. and Chew, E.  MorpheuS: Generating Structured Music with Constrained Patterns and Tension. IEEE Transactions of Affective Computing, PP (99). August 2017.
• Hashida, M., Nakamura, E. and Katayose, H. Constructing PEDB 2nd Edition: A Music Performance Database with Phrase Information. In Proceedings of the 14th Sound and Music Computing Conference (Espoo, Finland, July 5-8, 2017), pp. 359-364.
• Martinez Nieto, J. C. and Freeman, J. Expression Marks for Programming Interactive Music. In Proceedings of the Tenor 2017 International Conference on Technologies for Music Notation & Representation (A Coruña, Spain, May 24-26, 2017), pp. 125-130.

2016

• Herremans, D. and Chew, E. MorpheuS: Automatic Music Generation with Recurrent Pattern Constraints and Tension Profiles. In Proceedings of IEEE TENCON 2016 (Singapore, November 22-25, 2016).
• Déguernel, K., Vincent, E. and Assayag, G. Using Multidimensional Sequences For Improvisation In
  The OMax Paradigm. In Proceedings of the 13th Sound and Music Computing Conference (Hamburg, August 30 – September 3, 2016), pp. 117-122.
• Hamanaka, M., Hirata, K. and Toto, S. DeepGTTM-II: Automatic Generation of Metrical Structure Based on Deep Learning Technique. In Proceedings of the 13th Sound and Music Computing Conference (Hamburg, August 30 – September 3, 2016), pp. 203-210.
• Hajič Jr., J. et al. Further Steps Towards a Standard Testbed for Optical Music Recognition. In Proceedings of the 17th International Society for Music Information Retrieval Conference (New York, August 7-11, 2016), pp. 157-163.
• Eldridge, A., Hughes, E. and Kiefer, C. Designing Dynamic Networked Scores to Enhance the Experience of Ensemble Music Making. In Proceedings of the Tenor 2016 International Conference on Technologies for Music Notation & Representation (Cambridge, UK, May 27-29, 2016), pp. 193-199.

2015

• Gilbertson, S. Beyond iTunes: XML Boffins Target Sheet Music. The Register, December 30, 2015.
• Padilla, V. et al. Improving Optical Music Recognition by Combining Outputs from Multiple Sources. In Proceedings of the 16th International Society for Music Information Retrieval Conference (Málaga, October 26-30, 2015), pp. 517-523.
• Sutcliffe, R. et al. Relating Natural Language Text to Musical Passages. In Proceedings of the 16th International Society for Music Information Retrieval Conference (Málaga, October 26-30, 2015), pp. 524-530.
• Kahn, N. U. and Lee, J-C. Singing Voice Synthesis Using HMM Based TTS and MusicXML. Journal of the Korea Society of Computer and Information, 20 (5), 2015, pp. 53-63.
• Baptiste-Jessel, N. Access to Musical Information for Blind People. In Proceedings of the Tenor 2015 International Conference on Technologies for Music Notation & Representation (Paris, May 28-30, 2015), pp. 232-236.
• Sapp, C. Graphic to Symbolic Representations of Musical Notation. In Proceedings of the Tenor 2015 International Conference on Technologies for Music Notation & Representation (Paris, May 28-30, 2015), pp. 125-133.

2014

• Church, M. and Cuthbert, M. S. Improving Rhythmic Transcriptions Via Probability Models Applied Post-OMR. In Proceedings of the 15th International Society for Music Information Retrieval Conference (Taipei, October 27-31, 2014), pp. 643-647.
• Kirlin, P. B. A Data Set for Computational Studies of Schenkerian Analysis. In Proceedings of the 15th International Society for Music Information Retrieval Conference (Taipei, October 27-31, 2014), pp. 213-218.
• Sutcliffe, R. et al. The [email protected] Task at MediaEval 2014: Natural Language Queries on Classical Music Scores. In Working Notes Proceedings of the MediaEval 2014 Workshop (Barcelona, October 16-17, 2014).

2013

• Sébastien, V., Sébastien, D. and Conruyt, N. Annotating Works for Music Education: Propositions for a Musical Forms and Structures Ontology and a Musical Performance Ontology. In Proceedings of the 14th International Society for Music Information Retrieval Conference (Curitiba, Brazil, November 4-8, 2013), pp. 451-456.
• Gabriel, J. Large Data Sets & Recommender Systems: A Feasible Approach to Learning Music? In Proceedings of the Sound and Music Computing Conference 2013 (Stockholm, July 30-August 2, 2013), pp. 701-706.
• Housley, L. et al. Implementation Considerations in Enabling Visually Impaired Musicians to Read Sheet Music Using a Tablet. In Proceedings of COMPSAC 2013: IEEE 37th Annual Computer Software and Applications Conference (Kyoto, July 22-26, 2013), pp. 678-683.
• Doerfler, G. and Beck, R. An Approach to Classifying Four-Part Music. In Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition (Las Vegas, July 22-25, 2013).
• Hawkett, A. An Empirical Investigation of the Concept of Memes in Music Using Mass Data Analysis of String Quartets. Ph.D. thesis, The University of Huddersfield, March 2013.

2012

• Sébastien, V. et al. Score Analyzer: Automatically Determining Scores Difficulty Level for Instrumental E-Learning. In Proceedings of the 13th International Society for Music Information Retrieval Conference (Porto, Portugal, October 8-12, 2012), pp. 571-576.
• Housley, L. L. Dynamic Generation of Musical Notation from MusicXML Input on an Android Tablet. M.S. thesis, The Ohio State University, 2012.

2011

• Viro, V. Peachnote: Music Score Search and Analysis Platform. In Proceedings of the 12th International Society for Music Information Retrieval Conference (Miami, October 24-28, 2011), pp. 359-362.
• Surada, J. and Carver, N. Towards an Automated Composer of Popular Country Music. In Proceedings of 2011 International Conference on Artificial Intelligence (Las Vegas, July 18-21, 2011), Vol. I, pp. 397-403.
• Arora, N. MXMLiszt: a preliminary MusicXML digital library platform built on available open-source technologies. OCLC Systems & Services, 27 (4), pp. 298-316.

2010

• Hosken, D. An Introduction to Music Technology. New York: Routledge, 2010. MusicXML is discussed in Chapter 15 on music notation.
• Cuthbert, M. S. and Ariza, C. music21: A Toolkit for Computer-Aided Musicology and Symbolic Music Data. In Proceedings of ISMIR 2010 11th International Conference on Music Information Retrieval (Utrecht, Netherlands, August 9-13, 2010), pp. 637-642.
• Ariza, C. and Cuthbert, M. S. Modeling Beats, Accents, Beams, and Time Signatures Hierarchically with music21 Meter Objects. In Proceedings of the 2010 International Computer Music Conference (New York, June 1-5, 2010).
• Arora, N. Beyond Images: Encoding Music for Access and Retrieval. University of Alabama research paper for Master’s in Library and Information Science, Spring 2010.
• Kainhofer, R. A MusicXML Test Suite and a Discussion of Issues in MusicXML 2.0. In Proceedings of Linux Audio Conference 2010 (Utrecht, Netherlands, May 1-4, 2010).

2009

• Hamanaka, M. and Tojo, S. Interactive GTTM Analyzer. In Proceedings of ISMIR 2009 10th International Conference on Music Information Retrieval (Kobe, Japan, October 26-30, 2009), pp. 291-296.
• Kirlin, P. Using Harmonic and Melodic Analyses to Automate the Initial Stages of Schenkerian Analysis. In Proceedings of ISMIR 2009 10th International Conference on Music Information Retrieval (Kobe, Japan, October 26-30, 2009), pp. 423-428.
• Nichols, E., Morris, D., Basu, S. and Raphael, C. Relationships Between Lyrics and Melody in Popular Music. In Proceedings of ISMIR 2009 10th International Conference on Music Information Retrieval (Kobe, Japan, October 26-30, 2009), pp. 471-476.
• Ganseman, J., Scheunders, P. and D’haes, W. Using XML-Formatted Scores in Real-Time Applications. In Proceedings of ISMIR 2009 10th International Conference on Music Information Retrieval (Kobe, Japan, October 26-30, 2009), pp. 663-668.
• Nielsen, J. S. B. Statistical Analysis of Musical Corpora. Bachelor’s thesis, Dept. of Computer Science, University of Copenhagen, January 2009.

2008

• Gotoh, T., Minamikawa-Tachino, R. and Tamura, N. A Web-Based Braille Translation for Digital Music Scores. In Proceedings of ASSETS 2008 10th International ACM SIGACCESS Conference on Computers and Accessibility (Halifax, October 13-15, 2008), pp. 259-260.
• Szwoch, M. Using MusicXML to Evaluate Accuracy of OMR Systems. In Diagrammatic Representation and Inference: Proceedings of Diagrams 2008 (Herrsching, Germany, September 19-21, 2008), Springer-Verlag, Berlin, pp. 419-422. Lecture Notes in Computer Science, Vol. 5223.
• Ganseman, J., Scheunders, P. and D’haes, W. Using XQuery on MusicXML Databases for Musicological Analysis. In Proceedings of ISMIR 2008 9th International Conference on Music Information Retrieval (Philadelphia, September 14-18, 2008), pp. 427-432.
• Capela, A., Cardoso, J. S., Rebelo, A. and Guedes, C. Integrated Recognition System for Music Scores. In Proceedings of the 2008 International Computer Music Conference (Belfast, August 24-29, 2008).
• Kuzmich, J., Jr. Integrating Power-User Applications: Part 2 of 2. School Band and Orchestra, April 2008, pp. 40-45.
• Kuzmich, J., Jr. Music Tech Integration with Power-User Applications: Part 1 of 2. School Band and Orchestra, March 2008.
• Williams, D. B. and Webster, P. R. Experiencing Music Technology, Updated Third Edition. Schirmer Books, 2008. MusicXML is discussed in Module 19 on Coding Systems for Music Notation and Performance.

2007

• Knopke, I. and Byrd, D. Towards Musicdiff: A Foundation for Improved Optical Music Recognition Using Multiple Recognizers. In Proceedings of ISMIR 2007 8th International Conference on Music Information Retrieval (Vienna, September 23-27, 2007), pp. 123-126.
• Barrett, G. D., Winter, M. and Wulfson, H. Automatic Notation Generators. In Proceedings of the 2007 International Computer Music Conference (Copenhagen, August 27-31, 2007).
• Vigliante, R. MusicXML: An XML Based Approach to Automatic Musicological Analysis. In Proceedings of Digital Humanities 2007 (Urbana-Champaign, IL, June 4-8, 2007).
• Clemmons, B. The Dictionary of North American Hymnology: Creating the Twenty-First Century Index of North American Hymnody. Choral Journal,  47 (9), March 2007, pp. 75-78.
• Goto, D., Gotoh, T., Minamikawa-Tachino, R. and Tamura, N. A Transcription System from MusicXML Format to Braille Music Notation. EURASIP Journal on Advances in Signal Processing, vol. 2007, Article ID 42498, 9 pages, 2007.
• Mullins, K. and Cahill, M. Importing MusicXML files into Max/MSP. Technical Report UL-CSIS-07-01, University of Limerick, 2007.

2006

• Selfridge-Field, E. XML Applications in Music Scholarship. In Music Analysis East and West, W. B. Hewlett and E. Selfridge-Field, eds., MIT Press, Cambridge, MA, 2006, pp. 21-40. Computing in Musicology 14.
• Dehghani, M. and Lovett, A. M. Efficient Genre Classification Using Qualitative Representations. In Proceedings of ISMIR 2006 7th International Conference on Music Information Retrieval (Victoria, Canada, October 8-12, 2006), pp. 353-354.
• Cunningham, S., Gebert, N., Picking, R. and Grout, V. Web-Based Music Notation Editing. In Proceedings of the IADIS International Conference on WWW/Internet 2006 (Murcia, Spain, October 5-8, 2006).

2005

• Bellmann, H. About the Determination of Key of a Musical Excerpt. In Proceedings of the Third International Symposium on Computer Music Modeling and Retrieval (Pisa, September 26-28, 2005), Springer-Verlag, Heidelberg, pp. 76-91. Lecture Notes in Computer Science, Vol. 3902.
• Hamilton, R. The jChing: A Java-Based Algorithmic Composition Tool. In Proceedings of the 2005 International Computer Music Conference (Barcelona, September 5-9, 2005).
• Jewell, M. O., Nixon, M. S., and Prügel-Bennett, A. State-Based Sequencing: Directing the Evolution Of Music. In Proceedings of the 2005 International Computer Music Conference (Barcelona, September 5-9, 2005).
• Jewell, M. O., Middleton, L., Nixon, M. S., Prügel-Bennett, A. and Wong, S. C. A Distributed Approach to Musical Composition. In Proceedings of 9th International Conference on Knowledge-Based & Intelligent Information & Engineering Systems KES 2005 (Melbourne, September 14-16, 2005).
• Sapp, C. S. Online Database of Scores in the Humdrum File Format. In Proceedings of ISMIR 2005 6th International Conference on Music Information Retrieval (London, September 11-15, 2005), pp. 664-665.
• McCann, W. New Tools For Transcribers And Blind Musicians From Dancing Dots And Duxbury. In Proceedings of the Technology and Persons with Disabilities Conference 2005 (Los Angeles, March 14-19, 2005).

2004

• Baird, K. C. Generating Music Notation in Real Time. Linux Journal, No. 128, December 2004, pp. 72-76.
• Kaji, K. and Nagao, K. MiXA: A Musical Annotation System. Demo paper from 3rd International Semantic Web Conference (Hiroshima, November 7-11, 2004).
• Didkovsky, N. Java Music Specification Language, V103 Update. In Proceedings of the 2004 International Computer Music Conference (Miami, November 1-6, 2004).
• Stevens, A. Band-In-A-Box, Finale, & MusicXML. Dr. Dobb’s Journal, 29 (9), September 2004, pp. 52-56.
• Kahlisch, T., Leopold, M. and Waldvogel, C. DaCapo, A Project on Transforming Ink Printed to Braille Notes Semi-Automatically: The Project’s Current State. In Proceedings of the 9th International Conference on Computers Helping People with Special Needs (Paris, July 7-9, 2004), Springer-Verlag, Heidelberg, pp. 224-227. Lecture Notes in Computer Science, Vol. 3118.

2003

• Stewart, D. XML for Music: A Markup Language That Breaks Down Musical Barriers. Electronic Musician, 19 (13), December 2003, pp. 58-64.
• Hirata, K., Noike, K. and Katayose, H. Proposal for a Performance Data Format. In Working Notes of IJCAI-03 Workshop on methods for automatic music performance and their applications in a public rendering contest (Acapulco, August 11, 2003).
• Santana, H., Dahia, M., Lima, E. and Ramalho, G. VExPat: An Analysis Tool for the Discovery of Musical Patterns. IX Simpósio Brasileiro de Computação Musical – Brazilian Symposium on Computer Music (Campinas, August 6-8, 2003).
• Cunningham, S. Music File Formats and Project XEMO. MSc thesis, University of Paisley, 2003.

2002

• Clemmons, W. New Standards and Emerging Technologies: A Rhythm Tutor with MusicXML and Finale. Association for Technology in Music Instruction (ATMI) Annual Conference (Kansas City, September 26-29, 2002).
• Tremblay, G. and Champagne, F. Automatic Marking of Musical Dictations By Applying the Edit Distance Algorithm On a Symbolic Music Representation. In Proceedings First International Conference MAX 2002: Musical Application Using XML (Milan, September 19-20, 2002), pp. 11-17.

In German

• Lehmann, A. Automatisiertes Motivsuchen in Musikwerken im MusicXML Format. Diplomarbeit, Humboldt-Universität zu Berlin, June 2009.
• Albrecht-Hohmaier, M. Komponist und Computer – philologische Konsequenzen zeitgenössischen Komponierens. In Vom Erkennen des Erkannten: Musikalische Analyse und Editionsphilologie. Festschrift für Christian Martin Schmidt, F. Wißmann, T. Ahrend, and H. von Loesch, eds. Breitkopf & Härtel, 2007, pp. 549-554.
• Lehmann, A. Maschinelles Komponieren – Automatisiertes Berechnen von Mittelstimmen in einem Kantionalsatz mit Hilfe von MusicXML und SimpleXML. Studienjahresarbeit, Humboldt-Universität zu Berlin, May 2007.
• Schnieders, R. Von der Quelle zum (Daten-)Fluss: Neue Medien in der Editionswissenschaft. Das Orchester, January 2004.
• Veit, J. Hase order Igel? – Musikeditionen une neue Medien. In “Alte” Musik und “neue” Medien, Georg Ulms Verlag, Hildesheim, 2003.

In Japanese

• Abe, R., Han, D., Tamura, N. and Gotoh, T. Building an Automated Analysis System to Support Proofreading Braille Music Notation. IEICE Transactions on Information and Systems (Japanese Edition), Vol. J92-D, No. 4, April 2009, pp. 480-490.

In other languages

• Tangari, N. Standard e documenti musicali. I numeri, I modelli, I formati (Standards and musical documents: Numbers, models, formats). Bibliografica, Milan, 2002.