Many congratulations to Katelyn Emerson for her recent article in Transactions of the International Society for Music Information Retrieval entitled 'Multimodal datasets for studying expert performances of musical scores'! This article comes from Katelyn's ongoing PhD research into the multimodal study of organ performance.
Multimodal datasets are datasets that provide multiple complementary streams of data corresponding to different recording modalities. In the context of music performance, a multimodal dataset might include modalities such as audio, musical scores, motion-capture data, physiological data, performer biography data, and so on. Collecting such diverse data can greatly expand the range of research questions we can ask about musical performance, especially those that look outside the details of note onsets and offsets and connect more widely with contextual attributes of the composition, performer, and performance.
This paper provides a comprehensive review of existing multimodal datasets for studying expert performances of musical scores. It provides a detailed organisation scheme for categorising these datasets, and identifies key challenges remaining for the collection of such datasets.
Check out the paper to learn more!
Emerson, K., & Harrison, P. M. C. (2025). Multimodal datasets for studying expert performances of musical scores. Transactions of the International Society for Music Information Retrieval, 8(1), 400–428. https://doi.org/10.5334/tismir.230