Mini-projects

In Concert: Towards a Collaborative Digital Archive of Musical Ephemera

Prof Rachel Cowgill (University of Huddersfield), Prof Alan Dix (University of Birmingham), Dr Rupert Ridgewell (British Library), Prof Simon McVeigh (Goldsmiths, University of London) and Prof Christina Bashford (University of Illinois at Urbana-Champaign)

This project was a collaboration between four musicologists (Cowgill, Ridgewell, McVeigh, and Bashford) concerned with the creation and use of digital archives, and a technologist (Dix) with expertise in the design of human-centred systems and innovative data interfaces.

The project set out to transform processes and tools for the development, curation, and use of digital archives. The datasets focussed on all concern concert ephemera, but cover different periods (from the 18th to the early 20th century) and differing geographic extents (London vs all Europe), and are at different stages in the process of curation (from OCR scans to fully authoritative resource). This offers a musicological opportunity to augment the individual datasets and interlink them, so that questions concerning the long-term evolution of public musical performance can be addressed that no single dataset can answer on its own.

The project chose a small number of very specific musicological questions – for example, 'how do the sites for musical performance in London change over time in terms of geographical distribution and audience demographic?' – each addressed using bespoke technical and human methods, but selecting questions to include a range of technical issues as well as musicological ones.

Selected key papers:

Terhi Nurmikko-Fuller, Alan Dix, David M. Weigl, and Kevin R. Page (August 2016). ‘In Collaboration with In Concert: Reflecting a Digital Library as Linked Data for Performance Ephemera’. In Proceedings of the Third International Workshop on Digital Libraries for Musicology (DLfM 2016). New York, NY. [acm |DOI:10.1145/2970044.2970049]

Alan Dix, Rachel Cowgill, Christina Bashford, Simon McVeigh, and Rupert Ridgewell (September 2014). ‘Authority and Judgement in the Digital Archive’. In Proceedings of the First International Workshop on Digital Libraries for Musicology (DLfM 2014). London. [acm |DOI:10.1145/2660168.2660171]

Characterising stylistic interpretations through automated analysis of ornamentation in Irish traditional music recordings

Dr Münevver Köküer (Birmingham City University), Dr Peter Jančovič (University of Birmingham), Mr Islah Ali-MacLachlan, Prof Cham Athwal (Birmingham City University) and Dr Daithí Kearney (Dundalk Institute of Technology)

While 'tunes' in Irish traditional music are usually of simple and regular structure, the tradition allows for and applauds the creativity of the individual musician. The perceived skill, creativity and musicality of musicians in the Irish tradition is often related to the use of ornamentation and variation in performance. The ability to accurately represent and analyse stylistic features such as ornaments allow for the development of discourse related to several key ethnomusicological questions surrounding music making, musical heritage and cultural change.

The use of terminology related to concepts of musical style may vary but usually relate to the use of identifiable features of an individual's approach to the performance of music. The style of the individual performers may be based on their experience in the tradition; listening to or playing with other traditions, perhaps in a locality or on recordings, or the use of published sheet music. While the existence of many different styles in Irish traditional music is generally accepted, an accurate and objective analysis of musical style has not yet been developed and questions remain concerning the analysis of stylistic difference in Irish traditional music. Examples of such questions could be whether there are patterns in the use of ornamentation that are favoured by a particular performer, any variations of these patterns and if exist, can they be grouped in a meaningful way to inform the understanding of musical style in Irish traditional music and to what extent patterns of musical style involving ornamentation are imitated by other performers. These questions could be extended from individual stylistic differences to regional stylistic differences and to change at various points of time through the twentieth century. Answering these questions would inform significant debates amongst both academics and practitioners related to variances in individualistic and regional styles and acknowledgement of change over time in the tradition.

In order to reliably answer these questions, a large number of recordings including various performances by musicians would need to be analysed, compared and contrasted. Computational analysis methods would enable us to analyse that large amount of recordings.

This mini-project worked towards that goal, focussing on ornamentation, since it is a strong decisive stylistic determinant in Irish traditional music. By employing state-of-the-art music information retrieval methods and developing novel extensions of these methods, the system could begin to find what type of ornaments were used and where in the tunes they were realised. While this mini-project focussed on understanding individual stylistic differences, the outcomes of the project could, in future work, be extended to the analysis and characterisation of regional stylistic differences and change over time.

Selected key papers:

Peter Jančovič, Münevver Köküer, and Wrena Baptiste (October 2015). ‘Automatic transcription of ornamented Irish traditional flute music using hidden Markov models’. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR 2015). Málaga, Spain. [pdf]

Islah Ali-MacLachlan, Münevver Köküer, Peter Jančovič, and Cham Athwal (June 2015). ‘Towards the identification of Irish traditional flute players from commercial recordings’. In Proceedings of the International Workshop on Folk Music Analysis (FMA 2015). Paris, France. [archive |eprint]

Münevver Köküer, Peter Jančovič, Islah Ali-MacLachlan, and Cham Athwal (October 2014). ‘Automated detection of single- and multinote ornaments in Irish traditional flute playing’. In Proceedings of the International Society for Music Information Retrieval Conference (ISMIR 2014). Taipei, Taiwan. [pdf]

Münevver Köküer, Daithí Kearney, Islah Ali-MacLachlan, Peter Jančovič, and Cham Athwal (September 2014). ‘Towards the creation of digital library content to study aspects of style in irish traditional music’. In Proceedings of the First International Workshop on Digital Libraries for Musicology (DLfM 2014). London. [acm |DOI:10.1145/2660168.2660188]

Medieval Music, Big Data and the Research Blend

Prof Mark Everist, Dr Nicholas Gibbins and Dr Gregorio Bevilacqua (University of Southampton)

The conductus is one of the central genres of medieval music, and consists of settings of Latin rhythmic poetry set to newly-composed music in the period from 1100 to around 1400 and later. Despite the survival of around 900 poems and slightly fewer musical settings, issues around the context and function of the conductus have continued to prove elusive and subject to debate and dissent. During the AHRC-funded 'Cantum pulcriorem invenire (CPI)' project, haphazard and ad hoc exploitation of big data were used largely to clarify questions associated with establishing poetic texts, their meaning and translation. One significant by-product of this work was the emergence of intertextual relationships between the texts of the conductus and other texts (a single example documents the use of the poetry of a conductus in a contemporary chronicle – completely unknown and unique in the repertory which will be written up as such). The fundamental question this mini-project sought to address is how far this ad hoc exploitation of big data can be systematized by the use of the Semantic Web (SW), and how far the scattered examples of intertextuality so far discovered are replicated elsewhere in the repertory.

The research materials fall into two categories: source and target data. The source data – the texts of the conductus poems – have been digitised as part of the CPI project and exist in XML format. The target data – the big data which consists of the vast amount of digitised medieval text of all forms (chronicles, technical text, patristics, poetry) – exists de facto on the web and in a variety of searchable open-access formats. One slight complication – which merely results in a slightly multiplication of the algorithms in the search engine – is that some data have been systematically edited and placed behind a paywall: Patrologia latina is a case in point; this subset of our big data will have to be handled slightly differently to other open-access material.

The identification of texts and text fragments from the source data within the much larger target dataset provide a ranked list of correspondences between the conductus and other texts that a researcher can then process using a blend of manual and digital tools. This an information retrieval task, but the nature of the proposed dataset gives rise to an additional consideration: the target dataset contains errors that arise from transcription or optical character, affecting recall (some matching texts will be missed).

Large-scale corpus analysis of historical electronic music using MIR tools: Informing an ontology of electronic music and cross-validating content-based methods

Dr Nick Collins, Prof Peter Manning and Dr Simone Tarsitani (Durham University)

Electronic music has developed a rich history over many decades, most intensively since the second World War, with manifestations in art music and popular music spheres, and much experimental work in-between. The strong heritage of electronic music has been an increasing target of analysts, often featuring certain key works, whether Kontakte, Concret PH or Papa Sangre.

MIR tools offer the possibility to expand this endeavour to a larger database of historical recorded works, tracking audible key trends in compositional and technological endeavour, with an empirical methodology. Ironically, despite the machine-mediated creation of electronic music, automated analysis techniques have not previously been employed to any great degree. Admittedly, although inexhaustible and objective, machine audio analysis has certain limitations compared to the golden standard of human analysis. To provide grounding for this work, this mini-project linked to an existing project supplying human analysis of key works, helping to validate machine methods.

The lead investigator and co-investigator compiled a larger corpus of historical works, aiming for clear coverage of important works in electronic music history, with a balanced approach to experimental art music, and popular music works. Over the course of the project, a corpus of analyses was built up over the  database. The dual aims were for deeper musicological insight and theory construction on the one hand, but also to provide a core resource for future electronic music scholarship.