Outputs (6)

Towards an ‘Everything Corpus’: A Framework and Guidelines for the Curation of More Comprehensive Multimodal Music Data (2025)
Journal Article
Gotham, M., Bemman, B., & Vatolkin, I. (2025). Towards an ‘Everything Corpus’: A Framework and Guidelines for the Curation of More Comprehensive Multimodal Music Data. Transactions of the International Society for Music Information Retrieval, 8(1), 70-92. https://doi.org/10.5334/tismir.228

Music information retrieval (MIR) is increasingly concerned with properly managing the complexity of musical data and the curation of high-quality multimodal datasets for use in a variety of computational tasks. This article presents (1) a conceptual... Read More about Towards an ‘Everything Corpus’: A Framework and Guidelines for the Curation of More Comprehensive Multimodal Music Data.

Inner Metric Analysis as a Measure of Rhythmic Syncopation (2024)
Presentation / Conference Contribution
Bemman, B., & Christensen, J. (2024, November). Inner Metric Analysis as a Measure of Rhythmic Syncopation. Presented at ISMIR 2024: 25th International Society for Music Information Retrieval Conference, San Francisco

Ultrasonics and urban greening: an exploratory study on ultrasound presence in urban spaces (2024)
Journal Article
Grimshaw-Aagaard, M., & Bemman, B. (2024). Ultrasonics and urban greening: an exploratory study on ultrasound presence in urban spaces. Personal and Ubiquitous Computing, 28(5), 677-692. https://doi.org/10.1007/s00779-024-01798-5

Airborne ultrasound is a frequently overlooked feature of our environment as it is not audible to humans, and little is known of its health effects on humans. Presently, regulations governing noise pollution in urban areas concern only human-audible... Read More about Ultrasonics and urban greening: an exploratory study on ultrasound presence in urban spaces.

Inter-rater Agreement in Classifying Music According to a Guided Imagery and Music Taxonomy (2023)
Journal Article
Bemman, B., Bertelsen, L. R., Wärja, M., & Bonde, L. O. (2023). Inter-rater Agreement in Classifying Music According to a Guided Imagery and Music Taxonomy. Journal of Music Therapy, 60(3), 282–313. https://doi.org/10.1093/jmt/thad014

Machine learning in general practice: scoping review of administrative task support and automation (2023)
Journal Article
Sørensen, N. L., Bemman, B., Jensen, M. B., Moeslund, T. B., & Thomsen, J. L. (2023). Machine learning in general practice: scoping review of administrative task support and automation. BMC Primary Care, 24, Article 14. https://doi.org/10.1186/s12875-023-01969-y

Background
Artificial intelligence (AI) is increasingly used to support general practice in the early detection of disease and treatment recommendations. However, AI systems aimed at alleviating time-consuming administrative tasks currently appear l... Read More about Machine learning in general practice: scoping review of administrative task support and automation.

Backtracking search heuristics for solving the all-partition array problem (2019)
Presentation / Conference Contribution
Bemman, B., & Meredith, D. (2019, November). Backtracking search heuristics for solving the all-partition array problem. Presented at ISMIR 2019: International Society for Music Information Retrieval Conference, Delft University of Technology, Delft, Netherlands

Recent efforts to model the compositional processes of Milton Babbitt have yielded a number of computationally challenging problems. One of these problems, known as the \textit{all-partition array problem}, is a particularly hard variant of set cover... Read More about Backtracking search heuristics for solving the all-partition array problem.