ASyMMus at MTG Seminar, Universitat Pompeu Fabra Barcelona

The ASyMMus project and its integration into the DML web interface were presented by Daniel Wolff during his departmental talk on music similarity.

From the abstract:
The concept of similarity can be applied to music in a multitude of ways. Applications include systems which provide similarity estimates depending on the specific user and context as well as analysis tools that show similarity of music with regards to specified compositional, physical or contextual features. The ASyMMuS project allows musicologists to apply similarity analysis to musical corpora on a big-data infrastructure – allowing for a comparison of e.g. the works of a certain composer.

Read here for more information and the full abstract.

ASyMMuS Workshop on Audio-Symbolic Music Similarity Modelling

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 on the Digital Music Lab structure, the project’s aim is to promote a data driven approach to music similarity. This workshop will bring together researchers with different approaches to promote discussions on what constitutes and what contributes to music similarity.

For more information on the workshop, including programme, registration, and venue information, please visit the workshop webpage.

ASyMMuS at Lorentz Center Leiden Workshop on Music Similarity

Several researchers from the ASyMMus and DML projects prominently contributed to the high-profile international workshop “Music Similarity: Concepts, Cognition and Computation“.

The workshop gathered experts on music similarity from Computer Science, Musicology, Music Psychology and related scientific fields. In a highly-motivated series of workgroups and talks, our researchers collaborated with other experts in the field in theoretical concepts and computer models of music similarity.

Main areas that were addressed :
* Relationship of similarity and categorisation
* Embedding similarity in context
* Perception and cognition of similarity
* Similarity modelling
* Similarity in music content – music analysis
* Similarity in music expression

Results include a roadmap for interdisciplinary music similarity research as well as future collaborations across scientific fields.

DML and ASyMMuS projects at DMRN+9 workshop

Current progress on the DML and ASyMMuS projects will be presented at the Digital Music Research Network Workshop 2014 (DMRN+9), taking place on Tuesday 16th December at Queen Mary University of London. The list of project-related presentations is as follows:

  • “The ASyMMuS project: An integrated audio-symbolic model of music similarity”, Emmanouil Benetos, Daniel Wolff, Tillman Weyde (City University London), Nicolas Gold, Samer Abdallah (University College London) and Alan Marsden (Lancaster University)
  • “Towards analysing big music data – Progress on the DML research project”, Tillman Weyde, Stephen Cottrell, Jason Dykes, Emmanouil Benetos, Daniel Wolff, Dan Tidhar, Alexander Kachkaev (City University London), Mark Plumbley, Simon Dixon, Mathieu Barthet, Steven Hargreaves (Queen Mary University of London), Nicolas Gold, Samer Abdallah (University College London), Aquiles Alancr-Brayner, Mahendra Mahey and Adam Tovell (The British Library)

ASyMMuS project started!

ASyMMuS (“An Integrated Audio-Symbolic Model of Music Similarity”) is an AHRC project funded under the Amplification Awards call of the Digital Transformations in the Arts and Humanities Theme. This project aims to apply the newly developed technological infrastructure from the Digital Music Lab project, to answer the musicological question what constitutes and contributes to similarity of music. The £77k project (AH/M002454/1) is being carried out collaboratively between City University London, University College London, and Lancaster University.

For more information on the project, please visit the ASyMMuS proejct pages.