The works listed below are available as PDFs whenever permitted by copyright restrictions. Much of the corresponding research was done using various components of the jMIR research software package.

A number of early unpublished course papers are also available from my years as a student.

Academic Journal Articles

Vatolkin, I., and C. McKay. 2022. Multi-objective investigation of six feature source types for multi-modal music classification. Transactions of the International Society for Music Information Retrieval 5 (1): 1–19.

Cuenca, M. E., and C. McKay. 2021. Exploring musical style in the anonymous and doubtfully attributed mass movements of the Coimbra manuscripts: A statistical and machine learning approach. Journal of New Music Research 50 (3): 199–219.

McKay, C., J. Cumming, and I. Fujinaga. 2021. Lessons learned in a large-scale project to digitize and computationally analyze musical scores. Digital Scholarship in the Humanities 36 (s2): ii198–ii202.

McKay, C., and I. Fujinaga. 2007. Style-independent computer-assisted exploratory analysis of large music collections. Journal of Interdisciplinary Music Studies 1 (1): 63–85.

Wanderley, M., B. Vines, N. Middleton, C. McKay, and W. Hatch. 2005. The musical significance of clarinetists’ ancillary gestures: An exploration of the field. Journal of New Music Research 34 (1): 97–113.

Academic Book Chapters

McKay, C., and M. E. Cuenca. 2022. Influencias musicales en las misas y motetes de Cristóbal de Morales y Francisco Guerrero: Una aproximación estadística. In Musicología en transición, eds. J. Marín-López, A. Mazuela-Anguita and J. J. Pastor-Comín, 1031–1052. Madrid, Spain: Sociedad Española de Musicología.

Rodríguez-García, E., and C. McKay. 2021. Composer attribution of Renaissance motets: A case study using statistical features and machine learning. In The Anatomy of Iberian Polyphony Around 1500, eds. E. Rodríguez-García and J. P. d’Alvarenga, 401–38. Kassel, Germany: Edition Reichenberger.

McKay, C., and I. Fujinaga. 2013. Expressing musical features, class labels, ontologies, and metadata using ACE XML 2.0. In Structuring Music Through Markup Language: Designs and Architectures, ed. J. Steyn, 48–79. Hershey, PA: IGI Global.

Peer-Reviewed Academic Conference Publications

McKay, C. 2023. From jSymbolic 2 to 3: More musical features. Proceedings of the International Symposium on Computer Music Multidisciplinary Research. 752–755.

Vatolkin, I., and C. McKay. 2022. Stability of symbolic feature group importance in the context of multi-modal music classification. Proceedings of the International Society for Music Information Retrieval Conference. 469–476.

Cumming, J., and C. McKay. 2021. Using corpus studies to find the origins of the madrigal. Proceedings of the Future Directions of Music Cognition International Conference. 38–42.

Ju, Y., S. Margot, C. McKay, and I. Fujinaga. 2020. Automatic chord labeling: A figured bass approach. Proceedings of DLfM 2020: The 7th International Conference on Digital Libraries for Musicology. 27–31.

Ju, Y., S. Margot, C. McKay, L. Dahn, and I. Fujinaga. 2020. Automatic figured bass annotation using the new Bach Chorales Figured Bass dataset. Proceedings of the International Society for Music Information Retrieval Conference. 640–646.

Ju, Y., S. Margot, C. McKay, and I. Fujinaga. 2020. Figured bass encodings for Bach chorales in various symbolic formats: A case study. Music Encoding Conference Proceedings. 71–74.

Ju, Y., S. Howes, C. McKay, N. Condit-Schultz, J. Calvo-Zaragoza, and I. Fujinaga. 2019. An interactive workflow for generating chord labels for homorhythmic music in symbolic formats. Proceedings of the International Society for Music Information Retrieval Conference. 862–869.

Cumming, J., C. McKay, J. Stuchbery, and I. Fujinaga. 2018. Methodologies for creating symbolic corpora of Western music before 1600. Proceedings of the International Society for Music Information Retrieval Conference. 491–498.

McKay, C., J. Cumming, and I. Fujinaga. 2018. jSymbolic 2.2: Extracting features from symbolic music for use in musicological and MIR research. Proceedings of the International Society for Music Information Retrieval Conference. 348–354.

Barbosa, J., C. McKay, and I. Fujinaga. 2015. Evaluating automated classification techniques for folk music genres from the Brazilian Northeast. Proceedings of the 15th Brazilian Symposium on Computer Music. 3–12.

McKay, C. 2013. jProductionCritic: An educational tool for detecting technical errors in audio mixes. Proceedings of the International Society for Music Information Retrieval Conference. 71–76.

McKay, C., and D. Bainbridge. 2011. A musical web mining and audio feature extraction extension to the Greenstone digital library software. Proceedings of the International Society for Music Information Retrieval Conference. 459–464.

Angeles, B., C. McKay, and I. Fujinaga. 2010. Discovering metadata inconsistencies. Proceedings of the International Society for Music Information Retrieval Conference. 195–200.

McKay, C., J. A. Burgoyne, J. Hockman, J. B. L. Smith, G. Vigliensoni, and I. Fujinaga. 2010. Evaluating the genre classification performance of lyrical features relative to audio, symbolic and cultural features. Proceedings of the International Society for Music Information Retrieval Conference. 213–218.

McKay, C., and I. Fujinaga. 2010. Improving automatic music classification performance by extracting features from different types of data. Proceedings of the ACM SIGMM International Conference on Multimedia Information Retrieval. 257–266.

Vigliensoni, G., C. McKay, and I. Fujinaga. 2010. Using jWebMiner 2.0 to improve music classification performance by combining different types of features mined from the web. Proceedings of the International Society for Music Information Retrieval Conference. 607–612.

McKay, C., and I. Fujinaga. 2009. jMIR: Tools for automatic music classification. Proceedings of the International Computer Music Conference. 65–68.

McKay, C., J. A. Burgoyne, J. Thompson, and I. Fujinaga. 2009. Using ACE XML 2.0 to store and share feature, instance and class data for musical classification. Proceedings of the International Society for Music Information Retrieval Conference. 303–308.

Thompson, J., C. McKay, J. A. Burgoyne, and I. Fujinaga. 2009. Additions and improvements to the ACE 2.0 music classifier. Proceedings of the International Society for Music Information Retrieval Conference. 435–440.

McKay, C., and I. Fujinaga. 2008. Combining features extracted from audio, symbolic and cultural sources. Proceedings of the International Conference on Music Information Retrieval. 597–602.

McKay, C., and I. Fujinaga. 2007. jWebMiner: A web-based feature extractor. Proceedings of the International Conference on Music Information Retrieval. 113–114.

McEnnis, D., C. McKay, and I. Fujinaga. 2006. jAudio: Additions and improvements. Proceedings of the International Conference on Music Information Retrieval. 385–386.

McEnnis, D., C. McKay, and I. Fujinaga. 2006. Overview of OMEN. Proceedings of the International Conference on Music Information Retrieval. 7–12.

McKay, C., D. McEnnis and I. Fujinaga. 2006. A large publicly accessible prototype audio database for music research. Proceedings of the International Conference on Music Information Retrieval. 160–163.

McKay, C., and I. Fujinaga. 2006. jSymbolic: A feature extractor for MIDI files. Proceedings of the International Computer Music Conference. 302–305.

McKay, C., and I. Fujinaga. 2006. Musical genre classification: Is it worth pursuing and how can it be improved?. Proceedings of the International Conference on Music Information Retrieval. 101–106.

Fiebrink, R., C. McKay, and I. Fujinaga. 2005. Combining D2K and JGAP for efficient feature weighting for classification tasks in music information retrieval. Proceedings of the International Conference on Music Information Retrieval. 510–513.

McEnnis, D., C. McKay, I. Fujinaga, and P. Depalle. 2005. jAudio: A feature extraction library. Proceedings of the International Conference on Music Information Retrieval. 600–603.

McKay, C., R. Fiebrink, D. McEnnis, B. Li, and I. Fujinaga. 2005. ACE: A framework for optimizing music classification. Proceedings of the International Conference on Music Information Retrieval. 42–49.

McKay, C., D. McEnnis, R. Fiebrink, and I. Fujinaga. 2005. ACE: A general-purpose classification ensemble optimization framework. Proceedings of the International Computer Music Conference. 161–164.

McKay, C., and I. Fujinaga. 2005. Automatic music classification and the importance of instrument identification. Proceedings of the Conference on Interdisciplinary Musicology. CD-ROM.

Sinyor, E., C. McKay, R. Fiebrink, D. McEnnis, and I. Fujinaga. 2005. Beatbox classification using ACE. Proceedings of the International Conference on Music Information Retrieval. 672–675.

McKay, C., and I. Fujinaga. 2004. Automatic genre classification as a study of the viability of high-level features for music classification. Proceedings of the International Computer Music Conference. 367–370.

McKay, C. and I. Fujinaga. 2004. Automatic genre classification using large high-level musical feature sets. Proceedings of the International Conference on Music Information Retrieval. 525–530.

Peer-Reviewed Academic Conference Presentations (No Proceedings)

Cuenca, M. E., and C. McKay. 2023. The stylistic origin of the anonymous 16th century masses transcribed by Siro Cisilino (1903-1987) at the Fondazione Cini: A statistical and machine learning approach. Presented at the Medieval and Renaissance Music Conference.

McKay, C., J. Cumming, and I. Fujinaga. 2023. Rhythmic, melodic and vertical n-gram features as a means of studying symbolic music computationally. Presented at the Digital Humanities Conference.

Cuenca, M. E., and C. McKay. 2022. Musical influences on the masses of Pedro Fernández Buch (c. 1574-1648): A stylistic comparison using statistical analysis. Presented at the Medieval and Renaissance Music Conference.

McKay, C., and J. Cumming. 2022. Summary features as the basis for content-based queries of symbolic music repositories. Presented at the Congress of the International Association of Music Libraries, Archives and Documentation Centres.

Cuenca, M. E., and C. McKay. 2021. Influencias musicales en las misas y motetes de Cristóbal de Morales y Francisco Guerrero: Una aproximación estadística. Presented at the Congreso de la Sociedad Española de Musicología.

McKay, C., and M. E. Cuenca. 2021. Musical influences on the masses and motets of Cristóbal de Morales and Francisco Guerrero: A statistical approach. Presented at the Medieval and Renaissance Music Conference.

Rodriguez-Garcia, E., and C. McKay. 2021. Ave festiva ferculis: Exploring attribution by combining manual and computational analysis. Presented at the Medieval and Renaissance Music Conference.

McKay, C., R. Adamian, J. Cumming, and I. Fujinaga. 2020. Exploring Renaissance music using n-gram aggregates to summarize local musical content. Presented at the Medieval and Renaissance Music Conference.

Cuenca, M. E., and C. McKay. 2019. Análisis estadístico de misas ibéricas renacentistas a través del software jSymbolic. Presented at the El análisis musical actual: Marco teórico e interdisciplinariedad conference.

Cuenca, M. E., and C. McKay. 2019. Exploring musical style in the anonymous and doubtfully attributed mass movements of the Coimbra manuscripts: A statistical approach. Presented at the Medieval and Renaissance Music Conference.

Hopkins, E., Y. Ju, G. Polins Pedro, C. McKay, J. Cumming, and I. Fujinaga. 2019. SIMSSA DB: Symbolic music discovery and search. Poster presentation at the International Conference on Digital Libraries for Musicology.

Ju, Y., G. Polins Pedro, C. McKay, E. Hopkins, J. Cumming, and I. Fujinaga. 2019. Enabling music search and analysis: A database for symbolic music files. Presented at the Music Encoding Conference.

McKay, C., E. Hopkins, G. Polins Pedro, Y. Ju, A. Kam, J. Cumming, and I. Fujinaga. 2019. A collaborative symbolic music database for computational research on music. Presented at the Medieval and Renaissance Music Conference.

McKay, C., J. Cumming, and I. Fujinaga. 2019. Lessons learned in a large-scale project to digitize and computationally analyze musical scores. Presented at the Digital Humanities Conference.

Cumming, J., and C. McKay. 2018. Revisiting the origins of the Italian madrigal using machine learning. Presented at the Medieval and Renaissance Music Conference.

Fujinaga, I., J. Cumming, A. Hankinson, R. Krämer, C. McKay, P. Schubert, and J. Wild. 2017. Large-corpus music research. Presented at the Congress of the International Musicology Society.

McKay, C., A. Hankinson, J. Cumming, and I. Fujinaga. 2017. A database model for computational music research. Poster presentation at the International Workshop on Digital Libraries for Musicology.

McKay, C., J. Cumming, and I. Fujinaga. 2017. Characterizing composers using jSymbolic2 features. Extended Abstracts for the Late-Breaking Demo Session of the 18th International Society for Music Information Retrieval Conference.

McKay, C., T. Tenaglia, J. Cumming, and I. Fujinaga. 2017. Using statistical feature extraction to distinguish the styles of different composers. Presented at the Medieval and Renaissance Music Conference.

McKay, C., T. Tenaglia, and I. Fujinaga. 2016. jSymbolic2: Extracting features from symbolic music representations. Extended Abstracts for the Late-Breaking Demo Session of the 17th International Society for Music Information Retrieval Conference.

McKay, C., and I. Fujinaga. 2015. Building an infrastructure for a 21st-century global music library. Extended Abstracts for the Late-Breaking Demo Session of the 16th International Society for Music Information Retrieval Conference.

Fujinaga, I., and C. McKay. 2008. ACE: Autonomous Classification Engine. Presented at the International Conference on Music Perception and Cognition.

Fujinaga, I., J. A. Burgoyne, C. Lai, B. Li, C. McKay, and L. Pugin. 2007. Distributed Digital Music Archives and Libraries (DDMAL). Presented at the Joint Conference of the Canadian Association of Music Libraries and the Association of Quebec Music Libraries.

McKay, C., and I. Fujinaga. 2006. Style-independent computer-assisted exploratory analysis of large music collections. Presented at the Joint Meeting of the American Musicological Society and the Society for Music Theory.

McKay, C. 2005. Approaches to overcoming problems in interactive musical performance systems. Presented at the McGill Graduate Students Society Symposium.

McKay, C., and I. Fujinaga. 2005. The Bodhidharma system and the results of the MIREX 2005 symbolic genre classification contest. Poster presented at the International Conference on Music Information Retrieval MIREX Session.

McKay, C. 2004. Issues in automatic musical genre classification. Presented at the McGill Graduate Students Society Symposium.

International Invited Academic Publications and Presentations

McKay, C. 2021. Exploring composer attribution in motet cycles using machine learning. Gaffurius Codices Online, Schola Cantorum Basiliensis.

McKay, C. 2021. What can MIR teach us about music? What can music teach us in MIR?. Presented at the Women in Music Information Retrieval (WiMIR) Workshop.

McKay, C. 2020. Digital musicology via jSymbolic and machine learning. Invited Speaker. Brandeis University, Waltham, USA. 3 March 2020.

McKay, C. 2019. SIMSSA DB: A collaborative musicological research database. Presented at the Digital Humanities Conference Digital Musicology Study Group.

McKay, C., and M. E Cuenca. 2019. CRIM, machine learning and big data: A case study on the Coimbra manuscripts. Presented at the Counterpoints: Renaissance Music and Scholarly Debate in the Digital Domain conference.

Cumming, J., and C. McKay. 2018. Contrapuntal style: Josquin Desprez vs. Pierre de la Rue. Presented at the Conference on Pierre de la Rue and Music at the Habsburg-Burgundian Court.

McKay, C. 2018. jSymbolic: A software application for music information retrieval and analysis. Invited Speaker. CESEM, Nova University of Lisbon, Lisbon, Portugal. 8 March 2018.

McKay, C. 2018. Performing statistical musicological research using jSymbolic and machine learning. Presented at The Anatomy of Polyphonic Music around 1500 International Conference.

McKay, C. 2018. SIMSSA DB: A database for computational musicological research. Presented at the Congress of the International Association of Music Libraries, Archives and Documentation Centres SIMSSA Workshop.

McKay, C. 2012. Classifying music with jMIR. Invited Speaker. Department of Languages and Science of Computation, University of Malaga, Spain. 10 January 2012.

McKay, C., J. A. Burgoyne, and I. Fujinaga. 2009. jMIR and ACE XML: Tools for performing and sharing research in automatic music classification. Presented at the ACM/IEEE Joint Conference on Digital Libraries Workshop on Integrating Digital Library Content with Computational Tools and Services.

McKay, C., J. Frank, and J. Turel. 2007. Audiofile: No box, no limit. Presented at Pop & Policy 2007: Music Fast Forward.

Local Invited Academic Presentations

McKay, C. 2024. LinkedMusic, SIMSSA DB and feature-based musicology. Presented at the CIRMMT Workshop on GLAM-MIR (Galleries, Libraries, Archives, Museums and Music Information Research), McGill University, Montreal, Canada. 6 April 2024.

McKay, C. 2024. Using machine learning and statistical analysis to make musical discoveries. Presented at Honours Science Talks. Marianopolis College, Montreal, Canada. 8 February 2024.

McKay, C., and R. Mizrahi. 2023. SIMSSA DB: Go Jump in the (Data) Lake. Presented at the LinkedMusic Workshop, McGill University, Montreal, Canada. 21 October 2023.

McKay, C. 2023. Feature extraction, feature-indexed databases, features in musicology and evolution with feature; Also, features. Presented at the CIRMMT Scientific Event, McGill University, Montreal, Canada. 25 May 2023.

McKay, C. 2022. SIMSSA DB: An introduction. Presented at the CIRMMT LinkedMusic Workshop on Music Databases, McGill University, Montreal, Canada. 18 November 2022.

McKay, C. 2022. SIMSSA DB: Some details. Presented at the LinkedMusic Prjoect Meeting, McGill University, Montreal, Canada. 19 November 2022.

Cumming, J., C. McKay, N. Nápoles López, and S. Margot. 2019. Contrapuntal style: Pierre de la Rue vs. Josquin Des Prez. Presented at the CIRMMT Workshop on SIMSSA (Single Interface for Music Score Searching and Analysis), McGill University, Montreal, Canada. 21 Saturday 2019.

Hopkins, E., G. Polins Pedro, Y. Ju, C. McKay, J. Cumming, and I. Fujinaga. 2019. SIMSSA DB: A brief overview of the data model. Presented at the DACT (Digital Analysis of Chant Transmission) Workshop, McGill University, Montreal, Canada. 21 Saturday 2019.

McKay, C., and R. Adamian. 2019. jSymbolic in 2019: Updates and improvements. Presented at the CIRMMT Workshop on SIMSSA (Single Interface for Music Score Searching and Analysis), McGill University, Montreal, Canada. 21 Saturday 2019.

McKay, C. 2018. jSymbolic: Demonstration and tutorial. Presented at the CIRMMT Workshop on Digital Musicology, McGill University, Montreal, Canada. 27 April 2018.

McKay, C., J. Cumming, J. Stuchbery, and I. Fujinaga. 2018. Methodologies for creating symbolic early music corpora for musicological research. Presented at the CIRMMT Workshop on Digital Musicology, McGill University, Montreal, Canada. 27 April 2018.

McKay, C. 2017. Using statistical feature extraction and machine learning in musicological research. Presented at the CIRMMT Workshop on SIMSSA (Single Interface for Music Score Searching and Analysis), McGill University, Montreal, Canada. 7 August 2017.

McKay, C. 2016. jSymbolic 2: New developments and research opportunities. Presented at the CIRMMT Workshop on SIMSSA (Single Interface for Music Score Searching and Analysis), McGill University, Montreal, Canada. 24 September 2016.

McKay, C. 2013. Applying music information retrieval techniques to audio production education. Presented at the CIRMMT Research Seminar. McGill University, Montreal, Canada. 8 September 2013.

McKay, C. 2013. Combining symbolic and audio musical data: A music classification perspective. Presented at the CIRMMT Workshop on Symbolic Music Processing, Semantic Audio, and Music Information Retrieval, McGill University, Montreal, Canada. 15 November 2013.

McKay, C. 2010. Evaluating the performance of lyrical features relative to and in combination with audio, symbolic and cultural features. Presented at the CIRMMT Workshop on Music Information Retrieval and Cultural Data , McGill University, Montreal, Canada. 22 October 2010.

McKay, C. 2009. Using timbre to predict musical genre: Promising solution or dead end?. Presented at the CIRMMT Workshop on Timbre, McGill University, Montreal, Canada. 11 October 2009.

McKay, C. 2008. Combining feature types with jMIR. Poster presentation at the Montreal Music and Machine Learning Workshop, Université de Montréal, Montreal, Canada. 14 November 2008.

McKay, C. 2008. Combining features extracted from audio, symbolic, and cultural sources. Presented at the CIRMMT Music Technology Colloquium, McGill University, Montreal, Canada. 30 September 2008.

Theses

McKay, C. 2010. Automatic music classification with jMIR. Ph.D. Dissertation. McGill University, Canada.

McKay, C. 2004. Automatic genre classification of MIDI recordings. M.A. Thesis. McGill University, Canada.

McKay, C. 2002. SpeciesChecker: A system for automatically proofreading species counterpoint. Undergraduate Thesis. University of Guelph, Canada.

McKay, C. and T. M. Luong. 1998. Localization of mobile robots using magnetic fields. Undergraduate Thesis. McGill University, Canada.