Searching for musical features using natural language queries: the C@merata evaluations at MediaEval

Sutcliffe, Richard; Hovy, Eduard; Collins, Tom; Wan, Stephen; Crawford, Tim and Root, Deane. 2019. Searching for musical features using natural language queries: the C@merata evaluations at MediaEval. Language Resources and Evaluation, 53(1), pp. 87-140. ISSN 1574-020X [Article]

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Abstract or Description

Musicological texts about classical music frequently include detailed technical discussions concerning the works being analysed. These references can be specific (e.g. C sharp in the treble clef) or general (fugal passage, Thor’s Hammer).Experts can usually identify the features in question in music scores but a means of performing this task automatically could be very useful for experts and beginnersalike. Following work on textual question answering over many years as co-or-ganisers of the QA tasks at the Cross Language Evaluation Forum, we decided in 2013 to propose a new type of task where the input would be a natural language phrase, together with a music score in MusicXML, and the required output would be one or more matching passages in the score. We report here on 3 years of theC@merata task at MediaEval. We describe the design of the task, the evaluation methods we devised for it, the approaches adopted by participant systems and the results obtained. Finally, we assess the progress which has been made in aligning natural language text with music and map out the main steps for the future. The novel aspects of this work are: (1) the task itself, linking musical references to actual music scores, (2) the evaluation methods we devised, based on modified versions of precision and recall, applied to demarcated musical passages, and (3) the progress which has been made in analysing and interpreting detailed technical references to music within texts.

Item Type:


Identification Number (DOI):


Question answering, Natural language processing, Music information retrieval, Musicological analysis, MusicXML, Evaluation

Departments, Centres and Research Units:

Computing > Intelligent Sound and Music Systems


23 July 2018Accepted
12 August 2018Published Online
1 March 2019Published

Item ID:


Date Deposited:

12 Sep 2018 09:32

Last Modified:

19 Mar 2021 12:55

Peer Reviewed:

Yes, this version has been peer-reviewed.


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