Current progress on the DML project will be presented at the 9th Conference on Interdisciplinary Musicology (CIM 2014). CIM will take place on 4-6 December in Berlin, Germany. Project-related papers are listed below (click titles to download abstracts):

• Mathieu Barthet, Mark Plumbley, Alexander Kachkaev, Jason Dykes, Daniel Wolff and Tillman Weyde, Big Chord Data Extraction and Mining
• Alexander Kachkaev, Daniel Wolff, Mathieu Barthet, Mark Plumbley, Jason Dykes and Tillman Weyde, Visualising Chord Progressions in Music Collections: A Big Data Approach

Recent work on instrumentation recognition that was carried out as part of the DML project was presented at the Workshop on Musical Timbre, that took place on 14th November at Télécom ParisTech, in Paris, France. The talk was entitled “Instrument transcription & instrumentation recognition”.

For more information on our work in instrumentation recognition, please see our DLfM paper: http://openaccess.city.ac.uk/4076/

Current progress on the DML project will be presented by Stephen Cottrell at the 59th annual meeting of the Society for Ethnomusicology, taking place on 13-16 November in Pittsburgh, Pennsylvania. The abstract for the talk can be found below:

Ethnomusicology, Music Information Retrieval and Big Data

The application of Music Information Retrieval (MIR) techniques to large recorded corpuses of music beyond the Western traditions, taken at face value, appears to run contrary to many of the principles which ethnomusicologists have long held dear. Culturally decontextualised, and with all the problems that attach to specific recordings serving as single instantiations of otherwise diverse musical traditions, the large-scale computerised analysis of such recordings risks appearing to return the discipline to its comparative musicology roots. Nevertheless, some studies have been undertaken over recent years as part of what is sometimes termed ‘computational ethnomusicology’. What is gained is the possibility not only of the kinds of technologically-enhanced analytical exactitude which computers can provide, but also of large-scale comparative analyses both within and across cultures. These offer, for example, the prospect of revisiting on a more scientific basis earlier debates about human universals in music making, in addition to the more usual traits of pitch or melody extraction, semantic categorisation and similar. Thus far, however, MIR studies have generally concentrated on individual recordings or small collections, which do not comfortably facilitate large-scale comparisons. This paper will review some of the latest work being undertaken in the MIR field in relation to global music traditions, and consider the problems and possibilities such approaches present. It will also report on the latest results from an ongoing government-funded UK research project – the Digital Music Lab – which seeks to apply MIR techniques to musical Big Data, specifically focused on music beyond the Western traditions.

As part of the DML project, a paper on large-scale analysis of harpsichord temperament has been authored by Dan Tidhar, Simon Dixon, Emmanouil Benetos, and Tillman Weyde. The paper is entitled “The Temperament Police“, and has been published at the special issue of Early Music (Oxford University Press) on “Early Music and Modern Technology“.

You can view the open access paper as either PDF or HTML (thanks to the City University London Open Access Block Grant for supporting this open access publication).

UPDATE: There is also a supplementary webpage accompanying the article, which is located at http://dml.city.ac.uk/temperament/

Current progress and future directions of the DML project will be presented by Daniel Wolff and Adam Tovell at the British Library Labs Symposium 2014, taking place on Monday 3rd November 2014, at the British Library Conference Centre. More information on the DML presentation can be found below:

Digital Music Lab – Analysing Big Music Data
Daniel Wolff, Research Fellow for the Digital Music Lab project at the Music Informatics Research Group, City University London and Adam Tovell, Curator, Digital Music, British Library
The Digital Music Lab is developing research methods and software infrastructure for exploring and analysing large-scale music collections, and to provide researchers and users with datasets and computational tools to analyse music audio, scores and metadata. The team will present some of their initial findings including some startling visualisations.

Current work on the DML project was presented at the 15th International Society for Music Information Retrieval Conference (ISMIR 2014, Taipei, Taiwan):

• At the Late-breaking and demo session, we presented the demo/poster “Visualising chord progressions in music collections: a big data approach” (click on link for abstract)
• At the Unconference session, we organised a discussion on “Big Data for Music Analysis and Musicology” (click on link for meeting notes)

The DML project was presented at the event sponsored by the Audio Engineering Society, entitled “Cutting Edge Research – from City University and King’s College London”, which took place at City University on 14th October.

The event showcased cutting edge research from City University’s Music Informatics Research group and King’s College London’s Centre for Telecommunications Research. As part of the event, Tillman Weyde gave a talk on the group’s activities (including the DML project), and Dr Dan Tidhar presented the poster entitled “Big Data for Musicology and Music Retrieval”.

Current progress on the DML project will be presented at the 1st International Digital Libraries for Musicology workshop (DLfM 2014). DLfM will take place on 12th September at City University London. Project-related papers are listed below (click titles to download):

• Tillman Weyde, Stephen Cottrell, Jason Dykes, Emmanouil Benetos, Daniel Wolff, Dan Tidhar, Nicolas Gold, Samer Abdallah, Mark Plumbley, Simon Dixon, Mathieu Barthet, Mahendra Mahey, Adam Tovell, Aquiles Alancar-Brayner. Big Data for Musicology
• Daniel Wolff, Dan Tidhar, Emmanouil Benetos, Edouard Dumon, Srikanth Cherla, Tillman Weyde. Incremental Dataset Definition for Large Scale Musicological Research