苹果淫院

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Du samedi 5 octobre au mardi 8 octobre, le campus du centre-ville et le campus Macdonald ne seront accessibles qu鈥檃ux 茅tudiants et aux membres du personnel de l鈥橴niversit茅 苹果淫院, ainsi qu鈥檃ux visiteurs essentiels. De nombreux cours auront lieu en ligne. Le personnel devra travailler 脿 distance, si possible. Voir le site Web de la Direction de la protection et de la pr茅vention pour plus de d茅tails.

Event

CIRMMT Distinguished Lecture | Automatic music transcription and music understanding

Monday, November 21, 2022 17:00to18:00
Elizabeth Wirth Music Building Tanna Schulich Hall , 527 rue Sherbrooke Ouest, Montreal, QC, H3A 1E3, CA
Price: 
Free Admission

"Automatic music transcription and music understanding"

Simon Dixon, Professor, Queen Mary University of London (UK)

For more information visit


Abstract

Automatic music transcription is the task of creating a score representation (for example in Western common music notation) from an audio recording or live audio stream. Although research on this topic spans almost 50 years, progress in the last few years has been quite remarkable. The field has moved from a situation where data was scarce, methods were ad hoc, and there were no standard methodologies or datasets for comparing competing approaches, to the current state where data-rich models are trained and tested on standard benchmark datasets. Various transcription tasks are addressed, such as transcription of a single or multiple simultaneous instruments, and transcription of the main melody or the bass line, the chords or the lyrics. After discussing some of the methods we have developed and used for music transcription, I will give examples of the application of this technology for understanding human music-making, such as analysis of melodic patterns in jazz improvisation and of expressive timing in classical and jazz performance.

Biography

Prof. Simon Dixon is Director of the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (2019-2027) and Deputy Director of the Centre for Digital Music (2015-) at Queen Mary University of London. He has a PhD in Computer Science and LMusA diploma in Classical Guitar. He has 25 years of research experience and has published over 250 papers in the area of music informatics, including work on high-level music signal analysis, computational modelling of musical knowledge and the study of musical performance. He was President of the International Society for Music Information Retrieval (ISMIR), is founding Editor-in-Chief of the Transactions of ISMIR, and member of the EPSRC Peer Review College. He has been PI on grants from UKRI (EPSRC, ESRC, AHRC), the European Commission (H2020, FP7), JISC, Innovate UK, and industry-funded projects.

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