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City University MIRG | Music Informatics Research Group

Applications, Code and Datasets. Follow us on Twitter. Music Informatics Research Group. The Music Informatics research group is a specialized research team within the Department of Computer Science. Music information retrieval. Adaptive models of score, MIDI, and audio data, with the goal of genre classification, similarity, style and user modelling. Music signal analysis. Automatic music transcription, multi-pitch detection, onset detection, instrument identification. Play the funky music!

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City University MIRG | Music Informatics Research Group | mirg.city.ac.uk Reviews

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Applications, Code and Datasets. Follow us on Twitter. Music Informatics Research Group. The Music Informatics research group is a specialized research team within the Department of Computer Science. Music information retrieval. Adaptive models of score, MIDI, and audio data, with the goal of genre classification, similarity, style and user modelling. Music signal analysis. Automatic music transcription, multi-pitch detection, onset detection, instrument identification. Play the funky music!

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5 reading group

6 mirg mailing list

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8 people

9 publications

10 projects

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City University MIRG | Music Informatics Research Group | mirg.city.ac.uk Reviews

https://mirg.city.ac.uk

Applications, Code and Datasets. Follow us on Twitter. Music Informatics Research Group. The Music Informatics research group is a specialized research team within the Department of Computer Science. Music information retrieval. Adaptive models of score, MIDI, and audio data, with the goal of genre classification, similarity, style and user modelling. Music signal analysis. Automatic music transcription, multi-pitch detection, onset detection, instrument identification. Play the funky music!

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mirg.city.ac.uk

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Reading Group | City University MIRG

http://mirg.city.ac.uk/category/readinggroup

Applications, Code and Datasets. Follow us on Twitter. Digital Musicology Workshop @ Digital Humanities at Oxford Summer School (DHOxSS). Bull; June 3, 2015 • Reading Group. Read more →. Seminar by Polina Proutskova, Wed 24/09/2014, 12:00. Bull; September 15, 2014 • News. Read more →. Seminar by Florian Jouffreau, Wed 20th Aug, AG06, 4:30pm. Bull; August 19, 2014 • News. On Wednesday 20/8/2014, at 4:30pm, Florian Jouffreau (Polytech Paris UPMC, visiting MIRG) will give a talk entitled Particle Swarm Opti...

2

People | City University MIRG

http://mirg.city.ac.uk/people

Applications, Code and Datasets. Follow us on Twitter. Tillman Weyde (Senior Lecturer and Group Leader). Daniel Wolff (Research Fellow). Reinier de Valk (Research Student). Srikanth Cherla (Research Student). Andrew Lambert (Research Student). Andreas Jansson (Part-Time Research Student). Emmanouil Benetos (Honorary Visiting Fellow – former Research Fellow). Darrell Conklin (former Group Leader). Dan Tidhar (Research Fellow). Aline Honingh (former Research Fellow). Jens Wissmann (former Research Student).

3

Publications | City University MIRG

http://mirg.city.ac.uk/publications

Applications, Code and Datasets. Follow us on Twitter. Wolff, D., MacFarlane, A. and Weyde, T. (2015). Comparative Music Similarity Modelling Using Transfer Learning Across User Groups. In: 16th International Society for Music Information Retrieval Conference, pp. 24-30, Oct. 2015. De Valk, R., Weyde, T. (2015). Bringing ‘Musicque into the tableture’: Machine learning models for polyphonic transcription of sixteenth-century lute tablature. Early Music, accepted. Early Music, 42(4):579-590, Nov. 2014.

4

News | City University MIRG

http://mirg.city.ac.uk/category/news

Applications, Code and Datasets. Follow us on Twitter. ASyMMuS Workshop on Audio-Symbolic Music Similarity Modelling. Bull; June 29, 2015 • News. ASyMMuS Workshop on Audio-Symbolic Music Similarity Modelling 8 July 2015, 10:00 15:30 Foyle Suite, Centre for Conservation British Library The AHRC funded project on An Integrated Audio-Symbolic Model of Music Similarity (ASyMMuS) aims to integrate aspects of audio and symbolic representations, such as scores or MIDI data, in a joint model. By building. Bull; ...

5

DML Final Workshop on Analysing Big Music Data | City University MIRG

http://mirg.city.ac.uk/news/dml-final-workshop-on-analysing-big-music-data

Applications, Code and Datasets. Follow us on Twitter. DML Final Workshop on Analysing Big Music Data. Bull; March 5, 2015 • News. The Music Informatics group, as part of its AHRC-funded DML project. Is co-organising the workshop:. Digital Music Lab Final Workshop on Analysing Big Music Data. 13 March 2015, 10:00 16:30. Foyle Suite, Centre for Conservation. For more information on the workshop, including programme, registration, and venue information, please visit the workshop webpage.

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About - Andyroid - Andrew Elmsley (né Lambert) BA(hons) MSc

http://andyroid.co.uk/about

My name's Andrew Elmsley but you can call me Andy. I'm a software developer/musician/artist currently undertaking a PhD at City, University of London. My research is focused on machine perception of pulse and metre with time-varying tempo and expressive timing. You can find out more bout the Music Informatics group at City on our website. I'm available for freelance projects. And also offer private tuition. I live in sunny Brighton, England. In 2012 I graduated from Sussex University.

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City University MIRG | Music Informatics Research Group

Applications, Code and Datasets. Follow us on Twitter. Music Informatics Research Group. The Music Informatics research group is a specialized research team within the Department of Computer Science. Music information retrieval. Adaptive models of score, MIDI, and audio data, with the goal of genre classification, similarity, style and user modelling. Music signal analysis. Automatic music transcription, multi-pitch detection, onset detection, instrument identification. Play the funky music!

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