Recent interest in the preservation of our heritage has brought about increased archival research, which has made a considerable number of historical documents available in digital format. However, the analysis of these documents still greatly depends on manually intensive work by domain experts. Early music manuscripts are one of the most complicated sources as they require extensive knowledge of domain experts. Although optical music recognition has been actively investigated, it has; not been applied to music manuscripts from a historical musicological perspective. The principal aim of this work is to reveal the potential of music manuscripts as a source of data mining by integrating historical musicologists' knowledge. Particular attention is paid to the paleographical aspects of music manuscripts. Image processing is used to extract geometric features from music manuscripts and statistical analysis is conducted. The proposed methods are validated by exploring case studies in Bach source studies, the results of which suggest that there is a strong potential for them to become a road map not only for musicological research but also other empirical research. Moreover, the results of the proposed research may, also serve as a prototype for next-generation data mining, which can not only use the data-driven information but also the experts' background knowledge in highly professional subjects
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:602713 |
| Date | January 2013 |
| Creators | Niitsuma, Masahiro |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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