Simon Dixon: Automatic music transcription and music understanding

Simon Dixon: Automatic music transcription and music understanding

A Distinguished Lecture from Simon Dixon, Professor at Queen Mary University of London, UK

The lecture will take place in TANNA SCHULICH HALL, followed by a wine and cheese reception in the lobby of the Elizabeth Wirth Music Building. This event is free and open to the general public. 

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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.


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.