Towards automated discovery of knowledge from Bach's original manuscripts

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the preservation of our heritage has brought about increased archival research, which has made a considerable number of historical documents available in digital format.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. Ea...

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Main Author: Niitsuma, Masahiro
Published: Queen's University Belfast 2013
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602713
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spelling ndltd-bl.uk-oai-ethos.bl.uk-6027132015-03-20T04:52:50ZTowards automated discovery of knowledge from Bach's original manuscriptsNiitsuma, Masahiro2013Recent 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the preservation of our heritage has brought about increased archival research, which has made a considerable number of historical documents available in digital format.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 subjects006.4Queen's University Belfasthttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602713Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 006.4
spellingShingle 006.4
Niitsuma, Masahiro
Towards automated discovery of knowledge from Bach's original manuscripts
description 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
author Niitsuma, Masahiro
author_facet Niitsuma, Masahiro
author_sort Niitsuma, Masahiro
title Towards automated discovery of knowledge from Bach's original manuscripts
title_short Towards automated discovery of knowledge from Bach's original manuscripts
title_full Towards automated discovery of knowledge from Bach's original manuscripts
title_fullStr Towards automated discovery of knowledge from Bach's original manuscripts
title_full_unstemmed Towards automated discovery of knowledge from Bach's original manuscripts
title_sort towards automated discovery of knowledge from bach's original manuscripts
publisher Queen's University Belfast
publishDate 2013
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.602713
work_keys_str_mv AT niitsumamasahiro towardsautomateddiscoveryofknowledgefrombachsoriginalmanuscripts
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