Abstract
An application of relational case-based learning to the task of expressive music performance is presented. We briefly recapitulate the relational case-based learner DISTALL and empirically show that DISTALL outperforms a straightforward propositional k-NN on the music task. A set distance measure based on maximal matching – incorporated in DISTALL – is discussed in more detail and especially the problem associated with its ‘penalty part’: the distance between a large and a small set is mainly determined by their difference in cardinality. We introduce a method for systematically varying the influence of the penalty on the overall distance measure and experimentally test different variants of it. Interestingly, it turns out that the variants with high influence of penalty clearly perform better than the others on our music task.
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References
Bisson, G.: Learning in FOL with a Similarity Measure. In: Proceedings of the 10th AAAI (1992)
Arcos, J.L., de Mántaras, L.: An Interactive CBR Approach for Generating Expressive Music. Journal of Applied Intelligence 14(1), 115–129 (2001)
De Raedt, L.: Interactive Theory Revision: an Inductive Logic Programming Approach. Academic Press, London (1992)
Dzeroski, S., Schulze-Kremer, H.K.R., Siems, K., Wettschereck, D., Blockeel, H.: Diterpene structure elucidation from 13C NMR spectra with inductive logic programming. Applied Artificial Intelligence: Special Issue on First-Order Knowledge Discovery in Databases 12(5), 363–384 (1998)
Emde, D., Wettschereck, D.: Relational Instance-Base Learning. In: Proceedings of the Thirteen International Conference on Machine Learning (ICML 1996), pp. 122–130. Morgan Kaufmann, San Mateo (1996)
López de Mántaras, R., Arcos, J.L.: AI and Music: From Composition to Expressive Performances. AI Magazine 23(3), 43–57 (2002)
Mehlhorn, K.: Graph algorithms and NP-completeness. Data structures and algorithms, vol. 2. Springer, Heidelberg (1984)
Muggleton, S.H., Feng, C.: Efficient Induction of Logic Programs. In: Proceedings of the First Conference on Algorithmic Learning Theory, Tokyo (1990)
Ramon, J., Bruynooghe, M.: A Framework for defining distances between first-order logic objects. In: Page, D.L. (ed.) ILP 1998. LNCS, vol. 1446, pp. 271–280. Springer, Heidelberg (1998)
Ramon, J., Bruynooghe, M.: A polynomial time computable metric between point sets. Report CW 301, Department of Computer Science, K.U. Leuven, Leuven, Belgium (2000)
Rouveirol, C.: Extensions of inversion of resolution applied to theory completion. In: Muggleton, S. (ed.) Inductive Logic Programming, Academic Press, London (1992)
Tobudic, A., Widmer, G.: Playing Mozart Phrase By Phrase. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, Springer, Heidelberg (2003)
Tobudic, A., Widmer, G.: Relational IBL in Music with a New Structural Similarity Measure. In: Horváth, T., Yamamoto, A. (eds.) ILP 2003. LNCS (LNAI), vol. 2835, pp. 365–382. Springer, Heidelberg (2003)
Todd, N.M.: The Dynamics of Dynamics: A Model of Musical Expression. Journal of the Acoustical Society of America 91, 3540–3550 (1992)
Widmer, G., Tobudic, A.: Playing Mozart by Analogy: Learning Multi- Level Timing and Dynamics Strategies. Journal of New Musical Research 32(3), 259–268 (2003)
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Tobudic, A., Widmer, G. (2004). Case-Based Relational Learning of Expressive Phrasing in Classical Music. In: Funk, P., González Calero, P.A. (eds) Advances in Case-Based Reasoning. ECCBR 2004. Lecture Notes in Computer Science(), vol 3155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28631-8_31
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DOI: https://doi.org/10.1007/978-3-540-28631-8_31
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