Characterisation of harmony with inductive logic programming

ISMIR 2008 - 9th International Conference on Music Information Retrieval

Volumn , Issue , 2008, Pages 63-68

  Anglade, Amélie ^a   Dixon, Simon ^a  

^a QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HIGH-LEVEL INFORMATION; IN-DEPTH ANALYSIS; LOGICAL RULES; PRELIMINARY ANALYSIS;

INFORMATION RETRIEVAL;

INDUCTIVE LOGIC PROGRAMMING (ILP);

EID: 80053098601     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. M. J. Dovey. Analysis of Rachmaninoff's piano performances using inductive logic programming. In Proceedings of the European Conference on Machine Learning, pages 279-282. Springer-Verlag, 1995.
2. C. Harte, M. Sandler, S. Abdallah, and E. Gómez. Symbolic representation of musical chords: a proposed syntax for text annotations. In Proceedings of ISMIR 2005, pages 66-71, London, UK, 2005.
3. M. Mauch, S. Dixon, C. Harte, M. Casey, and B. Fields. Discovering chord idioms through Beatles and Real Book songs. In Proceedings of ISMIR 2007, pages 255-258, Vienna, Austria, 2007.
4. E. F. Morales. PAL: A pattern-based first-order inductive system. Machine Learning, 26: 227-252, 1997.
5. S. Muggleton. Inductive logic programming. New Generation Computing, 8 (4): 295-318, 1991.
6. P. J. Ponce de León, D. Rizo, and J. M. Iñesta. Towards a human-friendly melody characterization by automatically induced rules. In Proceedings of ISMIR 2007, pages 437-440, Vienna, Austria, 2007.
7. Y. Raimond, S. Abdallah, and M. Sandler. The Music Ontology. In Proceedings of ISMIR 2007, pages 417-422, Vienna, Austria, 2007.
8. R. Ramirez. Inducing musical rules with ILP. In Proceedings of the International Conference on Logic Programming, pages 502-504. Springer-Verlag (LNCS)), 2003.
9. R. Ramirez and A. Hazan. A tool for generating and explaining expressive music performances of monophonic jazz melodies. International Journal on Artificial Intelligence Tools, 15 (4): 673-691, 2006.
10. R. Ramirez, A. Hazan, E. Gómez, and E. Maestre. Understanding expressive transformations in saxophone jazz performances using inductive machine learning. In Proceedings Sound and Music Computing International Conference, Paris, 2004.
11. A. Srinivasan. The Aleph Manual (version 4), 2003.
12. D. Temperley and D. Sleator. Modeling meter and harmony: A preference-rule approach. Computer Music Journal, 23 (1): 10-27, 1999.
13. E. Van Baelen and L. De Raedt. Analysis and prediction of piano performances using Inductive Logic Programming. In Proceedings of the International Conference in Inductive Logic Programming, pages 55-71, 1996.
14. P. van Kranenburg. Composer attribution by quantifying compositional strategies. In Proceedings of ISMIR 2006, Victoria, Canada, 2006.
15. various. The Real Book. Hal Leonard Corporation, 6th edition, 2004.
16. G. Widmer. Discovering simple rules in complex data: A meta-learning algorithm and some surprising musical discoveries. Artificial Intelligence, 146 (2): 129-148, 2003.