Towards Musicologist-driven Mining of Handwritten

Date
2017-12-31
Authors
Niitsuma, M
Yan, W-Q
Tomita, Y
Bell, D
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers
Abstract

Historical musicologists have been seeking for objective and powerful techniques to collect, analyse and verify their findings for many decades. The aim of this study was to show the importance of such domain-specific problems to achieve actionable knowledge discovery in the real the world. Our focus is on finding evidence for the chronological ordering of J.S. Bach’s manuscripts, by proposing a musicologist-driven mining method for extracting quantitative information from early music manuscripts. Bach’s C- clefs were extracted from a wide range of manuscripts under the direction of domain experts, and with these the classification of C-clefs was conducted. The proposed methods were evaluated on a dataset containing over 1000 clefs extracted from J.S. Bach’s manuscripts. The results show more than 70% accuracy for dating J.S. Bach’s manuscripts. Dating of Bach’s lost manuscripts was quantitatively hypothesized, providing a rough barometer to be combined with other evidence to evaluate musicologists’ hypotheses, and the practicability of this domain-driven approach is demonstrated.

Description
Keywords
Domain-driven data mining; Optical music recognition; Historical musicology; Music informatics; Music information retrieval
Source
IEEE Intelligent Systems, vol. 33, no. 4, pp. 24-34, Jul./Aug. 2018. doi: 10.1109/MIS.2018.111144115
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