SIARCT-CFP: Improving precision and the discovery of inexact musical patterns in point-set representations

Proceedings of the 14th International Society for Music Information Retrieval Conference, ISMIR 2013

Volumn , Issue , 2013, Pages 549-554

  Collins, Tom ^a   Arzt, Andreas ^a   Flossmann, Sebastian ^a   Widmer, Gerhard ^a  

^a JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

PATTERN MATCHING;

FALSE POSITIVE; GEOMETRIC APPROACHES; GEOMETRIC PATTERNS; PATTERN DISCOVERY; POINT SET; POLYPHONIC MUSIC; REPEATED PATTERNS; TIME-SPACE;

INFORMATION RETRIEVAL;

EID: 84904316629     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. T. Ahonen, K. Lemström, and S. Linkola: “Compression-based similarity measures in symbolic, polyphonic music,” Proceedings of the International Symposium on Music Information Retrieval, pp. 91–96, 2011.
2. A. Arzt, S. Böck, and G. Widmer: “Fast identification of piece and score position via symbolic fingerprinting,” Proceedings of the International Symposium on Music Information Retrieval, pp. 433–438, 2012.
3. I. Bent and A. Pople: “Analysis,” The new Grove dictionary of music and musicians, Macmillan, London, 2001.
4. T. Collins: “Discovery of repeated themes and sections,” Retrieved 4th May 2013, from http://www.music-ir.org/mirex/wiki/2013: Discovery of Repeated Themes %26 Sections
5. T. Collins: Improved methods for pattern discovery in music, with applications in automated stylistic composition, PhD thesis, Faculty of Mathematics, Computing and Technology, The Open University, 2011.
6. T. Collins, R. Laney, A. Willis, and P. Garthwaite: “Modeling pattern importance in Chopin’s mazurkas,” Music Perception, Vol. 28, No. 4, pp. 387–414, 2011.
7. T. Collins, J. Thurlow, R. Laney, A. Willis, and P. Garthwaite: “A Comparative Evaluation of Algorithms for Discovering Translational Patterns in Baroque Keyboard Works,” Proceedings of the International Symposium on Music Information Retrieval, pp. 3–8, 2010.
8. D. Conklin and C. Anagnostopoulou: “Representation and discovery of multiple viewpoint patterns,” Proceedings of the International Computer Music Conference, pp. 479–485, 2001.
9. D. Conklin and I. Witten: “Multiple viewpoint systems for music prediction,” Journal of New Music Research, Vol. 24, No. 1, pp. 51-73, 1995.
10. O. Lartillot and P. Toiviainen: “Motivic matching strategies for automated pattern extraction,” Musicae Scientiae, Discussion Forum 4A, pp. 281–314, 2007.
11. S. Livingstone, C. Palmer, and E. Schubert: “Emotional response to musical repetition,” Emotion, Vol. 12, No. 3, pp. 552–567, 2012.
12. A. Lubiw and L. Tanur: “Pattern matching in polyphonic music as a weighted geometric translation problem,” Proceedings of the International Symposium on Music Information Retrieval, pp. 154–161, 2004.
13. D. Meredith: “Point-set algorithms for pattern discovery and pattern matching in music,” Proceedings of the Dagstuhl Seminar on Content-Based Retrieval, 2006.
14. D. Meredith, K. Lemström, and G. Wiggins: “Algorithms for discovering repeated patterns in multidimensional representations of polyphonic music,” Journal of New Music Research, Vol. 31, No. 4, pp. 321–345, 2002.
15. E. Narmour: “Some major theoretical problems concerning the concept of hierarchy in the analysis of tonal music,” Music Perception, Vol. 1, No. 1, pp. 129–199, 1983.
16. C. Romming and E. Selfridge-Field: “Algorithms for polyphonic music retrieval: the Hausdorff metric and geometric hashing,” Proceedings of the International Symposium on Music Information Retrieval, pp. 457–462, 2007.
17. E. Ukkonen, K. Lemström, and V. Mäkinen: “Geometric algorithms for transposition invariant content-based music retrieval,” Proceedings of the International Symposium on Music Information Retrieval, pp. 193–199, 2003.
18. A. Wang: “An industrial strength audio search algorithm,” Proceedings of the International Symposium on Music Information Retrieval, pp. 7–13, 2003.