Gabriel Vigliensoni

Postdoctoral Researcher

Optical music recognition, AI-assisted music composition.

I have been professionally involved in music production, performance, and sound recording for several record labels and artists of diverse musical genres. The experience and the new music economy landscape created a desire to better understand the changing ways in which music is now created, distributed, and enjoyed. This desire led me to pursue a PhD in Music Technology. My main research interests are music composition, production, and sound engineering; music recommendation and listening behaviour; and new interfaces for musical expression, production, and synthesis.

Publications

Fujinaga, Ichiro, and Gabriel Vigliensoni. 2019. “The Art of Teaching Computers: The SIMSSA Optical Music Recognition Workflow System.” In Proceedings of the 27th European Signal Processing Conference. https://doi.org/10.23919/EUSIPCO.2019.8902658.
Vigliensoni, Gabriel, Jorge Calvo-Zaragoza, and Ichiro Fujinaga. 2018a. “An Environment for Machine Pedagogy: Learning How to Teach Computers to Read Music.” In Joint Proceedings of the ACM Intelligent User Interface Workshops: Intelligent Music Interfaces for Listening and Creation (MILC). Tokyo, Japan. http://cloud.simssa.ca/index.php/s/bBK9N6gQTpPaKkl.
Vigliensoni, Gabriel, Jorge Calvo-Zaragoza, and Ichiro Fujinaga. 2018b. “Developing an Environment for Teaching Computers to Read Music.” In Proceedings of 1st International Workshop on Reading Music Systems. Paris, France. http://cloud.simssa.ca/index.php/s/ImKlwsuLoI099uI.
Calvo-Zaragoza, Jorge, Francisco J. Castellanos, Gabriel Vigliensoni, and Ichiro Fujinaga. 2018. “Deep Neural Networks for Document Processing of Music Score Images.” Applied Sciences 8 (5):654. https://doi.org/10.3390/app8050654.
Castellanos, Francisco, Jorge Calvo-Zaragoza, Gabriel Vigliensoni, and Ichiro Fujinaga. 2018. “Document Analysis of Music Score Images with Selectional Auto Encoders.” In Proceedings of the 19th International Society for Music Information Retrieval Conference. Paris, France. http://cloud.simssa.ca/index.php/s/FjJGQ6josKEIWNn.
Nápoles López, Néstor, Gabriel Vigliensoni, and Ichiro Fujinaga. 2018. “Encoding Matters.” In Proceedings of the 5th International Conference on Digital Libraries for Musicology, 69–73. DLfM ’18. New York, NY, USA: ACM. https://doi.org/10.1145/3273024.3273027.
Vigliensoni, Gabriel, and Ichiro Fujinaga. 2017. “The Music Listening Histories Dataset.” In Proceedings of the International Society for Music Information Retrieva, 96–102. Suzhou, China. http://cloud.simssa.ca/index.php/s/HUvFrpFl0ErRVz9.
Vigliensoni, Gabriel. 2017. “Evaluating the Performance Improvement of a Music Recommendation Model by Using User-Centric Features.” PhD diss., Montreal, QC: McGill University. http://cloud.simssa.ca/index.php/s/QHcj2J9rQfM9fm8.
Calvo-Zaragoza, J., G. Vigliensoni, and I. Fujinaga. 2017. “Pixelwise Classification for Music Document Analysis.” In 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 1–6. https://doi.org/10.1109/IPTA.2017.8310134.
Calvo-Zaragoza, Jorge, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017a. “A Machine Learning Framework for the Categorization of Elements in Images of Musical Documents.” In Proceedings of the Third International on Technologies for Music Notation and Representation (TENOR 2017). La Coruña, Spain. http://cloud.simssa.ca/index.php/s/NExq8IWkue2IjCH.
Calvo-Zaragoza, Jorge, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017b. “One-Step Detection of Background, Staff Lines, and Symbols in Medieval Music Manuscripts with Convolutional Neural Networks.” In Proceedings of the International Society for Music Information Retrieval, 724–30. Suzhou, China. http://cloud.simssa.ca/index.php/s/JuPGmwlvAP9ckkR.
Calvo-Zaragoza, Jorge, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017c. “Pixel-Wise Binarization of Musical Document with Convolutional Neural Networks.” In Proceedings of the 15th IAPR International Conference on Machine Vision Applications, 362–65. Nagoya, Japan. http://cloud.simssa.ca/index.php/s/17ZXOEHz87iIzHM.
Calvo-Zaragoza, Jorge, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017d. “Staff-Line Detection on Grayscale Images with Pixel Classification.” In Pattern Recognition and Image Analysis, edited by Luís A. Alexandre, José Salvador Sánchez, and João M. F. Rodrigues, 279–86. Lecture Notes in Computer Science. Springer International Publishing. http://cloud.simssa.ca/index.php/s/tZswNa5gjwkoatf.
Calvo-Zaragoza, Jorge, Ké Zhang, Zeyad Saleh, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017. “Music Document Layout Analysis through Machine Learning and Human Feedback.” In 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 02:23–24. Tokyo, Japan. https://doi.org/10.1109/ICDAR.2017.259.
Saleh, Zeyad, Ké Zhang, Jorge Calvo-Zaragoza, Gabriel Vigliensoni, and Ichiro Fujinaga. 2017. “Pixel.Js: Web-Based Pixel Classification Correction Platform for Ground Truth Creation.” In Proceedings of the Twelfth IAPR International Workshop on Graphics Recognition, 2:39-40. Kyoto, Japan: Springer LNCS. http://cloud.simssa.ca/index.php/s/7rWLN8VW6lXL8i7.
Calvo-Zaragoza, Jorge, Gabriel Vigliensoni, and Ichiro Fujinaga. 2016. “Document Analysis for Music Scores via Machine Learning.” In Proceedings of the 3rd International Workshop on Digital Libraries for Musicology, 37–40. DLfM 2016. New York, NY, USA: ACM. https://doi.org/10.1145/2970044.2970047.
Vigliensoni, Gabriel, and Ichiro Fujinaga. 2014. “Identifying Time Zones in a Large Dataset of Music Listening Logs.” In Proceedings of the International Workshop on Social Media Retrieval and Analysis, 27–32. Gold Coast, Australia. http://cloud.simssa.ca/index.php/s/XHUtAQXBI8zEOyx.
Vigliensoni, Gabriel, Gregory Burlet, and Ichiro Fujinaga. 2013. “Optical Measure Recognition in Common Music Notation.” In Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR), 125–30. Curitiba, Brazil. http://cloud.simssa.ca/index.php/s/e91SMTDZgP7XtNd.
Hankinson, Andrew, John Ashley Burgoyne, Gabriel Vigliensoni, and Ichiro Fujinaga. 2012. “Creating a Large-Scale Searchable Digital Collection from Printed Music Materials.” In Proceedings of the World Wide Web Conference, 903–908. Lyon, FR. http://cloud.simssa.ca/index.php/s/g4kY4j3CzEa6vT6.
Hankinson, Andrew, John Ashley Burgoyne, Gabriel Vigliensoni, Alastair Porter, Jessica Thompson, Wendy Liu, Remi Chiu, and Ichiro Fujinaga. 2012. “Digital Document Image Retrieval Using Optical Music Recognition.” In Proceedings of 13th International Society for Music Information Retrieval Conference (ISMIR). Porto, Portugal. http://cloud.simssa.ca/index.php/s/YN1gYHw0mRor9rE.
Vigliensoni, Gabriel, John Ashley Burgoyne, Andrew Hankinson, and Ichiro Fujinaga. 2011. “Automatic Pitch Detection in Printed Square Notation.” In Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR), 423–28. Miami, FL. http://cloud.simssa.ca/index.php/s/yxAuJOiZau6LMOL.
Vigliensoni, Gabriel, Cory McKay, and Ichiro Fujinaga. 2010. “Using JWebMiner 2.0 to Improve Music Classification Performance by Combining Different Types of Features Mined from the Web.” In Proceedings of the International Society for Music Information Retrieval Conference, 607–12. Utrecht. http://cloud.simssa.ca/index.php/s/epYWZBSMmtbknUo.

Research Interests

  • Music production
  • Music composition
  • Music recommendation
  • Music listening behaviour
  • Optical music recognition

Academic Record

  • PhD in Music, McGill University
  • MA in Music Technology, McGill University
  • BA in Sound Science, Universidad de Chile