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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.12
- 수록면
- 838 - 843 (6page)
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This paper presents an algorithm for effective retrieval of score information to an input score image. The originality of the proposed algorithm is that it is designed to be robust to recognition errors by an OMR (Optical Music Recognition), while existing methods such as pitch histogram requires error induced OMR result be corrected before retrieval process. This approach helps people to retrieve score without training on music score for error correction. OMR takes a score image as input, recognizes musical symbols, and produces structural symbolic notation of the score as output, for example, in MusicXML format. Among the musical symbols on a score, it is observed that filled noteheads are rarely detected with errors with its simple black filled round shape for OMR processing. Barlines that separate measures also strong to OMR errors with its long uniform length vertical line characteristic. The proposed algorithm consists of a descriptor for a score and a similarity measure between a query score and a reference score. The descriptor is based on note-count, the number of filled noteheads in a measure. Each part of a score is represented by a sequence of note-count numbers. The descriptor is an n-gram sequence of the note-count sequence. Simulation results show that the proposed algorithm works successfully to a certain degree in score image-based retrieval for an erroneous OMR output.
목차
Abstract
I. Introduction
II. Existing work
III. Proposed algorithm
IV. Experimental results
V. Conclusion
References
참고문헌 (8)
참고문헌 신청
D. Garfinkle, C. Arthur, P. Shubert, J. Cumming and I. Fujinaga, "PatternFinder: Content-based Music Retrieval with music21," Proceedings of International Workshop on Digital Libraries for Musicology, Shanghai, China, pp. 5-8, October 2017.
T. Sikora, "The MPEG-7 visual standard for content description-an overview," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 6, pp. 696-702, June 2001.
H. Wang, Y. Cai, Y. Zhang, H. Pan, W. Lv and H. Han, "Deep Learning for Image Retrieval: What Works and What Doesn't," Proceedings of IEEE International Conference on Data Mining Workshop, Atlantic City, USA, pp. 1576-1583, November 2015.
C. McKay, J. E. Cumming and I. Fujinaga, "Jsymbolic2.2: extracting features from symbolic music for use in musicological and MIR research," Proceedings of 19th International Society for Music Retrieval Conference, Paris, France, pp. 348-354, September 2018.
A. Hankinson, J. A. Burgoyne, G. Vigliensoni, A. Porter, J. Thomson, W. Liu, R. Chiu and I. Fujinaga, "Digital document image retrieval using optical music recognition," Proceedings of 13th International Society for Music Retrieval Conference, Porto, Portugal, pp. 577-582, October 2012.
T. Sikora, "The MPEG-7 visual standard for content description-an overview," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 6, pp. 696-702, June 2001.
H. Wang, Y. Cai, Y. Zhang, H. Pan, W. Lv and H. Han, "Deep Learning for Image Retrieval: What Works and What Doesn't," Proceedings of IEEE International Conference on Data Mining Workshop, Atlantic City, USA, pp. 1576-1583, November 2015.
C. McKay, J. E. Cumming and I. Fujinaga, "Jsymbolic2.2: extracting features from symbolic music for use in musicological and MIR research," Proceedings of 19th International Society for Music Retrieval Conference, Paris, France, pp. 348-354, September 2018.
A. Hankinson, J. A. Burgoyne, G. Vigliensoni, A. Porter, J. Thomson, W. Liu, R. Chiu and I. Fujinaga, "Digital document image retrieval using optical music recognition," Proceedings of 13th International Society for Music Retrieval Conference, Porto, Portugal, pp. 577-582, October 2012.
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