Two grammatical inference applications in music processing

Applied Artificial Intelligence

Volumn 22, Issue 1-2, 2008, Pages 53-76

  Cruz Alcázar, Pedro P ^a   Vidal, Enrique ^a  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; IDENTIFICATION (CONTROL SYSTEMS); INFERENCE ENGINES; MATHEMATICAL MODELS; MULTIMEDIA SYSTEMS; STOCHASTIC CONTROL SYSTEMS;

AUTOMATIC COMPOSITION (AC); MULTIMEDIA DATABASES; MUSIC PROCESSING (MP); STOCHASTIC GRAMMARS;

COMPUTATIONAL GRAMMARS;

EID: 40149106291     PISSN: 08839514     EISSN: 10876545     Source Type: Journal    
DOI: 10.1080/08839510701853143     Document Type: Article

References (47)

1. Amengual, J. C. and E. Vidal. 1996. Two different approaches for cost-efficient viterbi parsing with error correction. In: Advances in Structural and Syntactic Pattern Recognition, eds. P. W. P. Perner and A. Rosenfeld, pp. 30-39. New York: Springer-Verlag.
2. Baggi, D. L. 1991. Computer-generated music. Computer Magazine, Vol. 24, No. 7, pp. 6-9.
3. Bod, R. 2002. A unified model of structural organization in language and music. Journal of Artificial Intelligence Research 17:289-308.
4. Cambouropoulos, E., T. Crawford, and C. S. Iliopoulos. 2001. Pattern processing in melodic sequences. Computen and the Humanities 35(1):9-21.
5. Carrasco, R. C. and J. Oncina. 1994. Learning stochastic regular grammars by means of a state merging method. In: Grammatical Inference and Applications, eds. R. C. Carrasco and J. Oncina, Lecture Notes in Artificial Intelligence (862). New York: Springer- Verlag.
6. Clarkson, P. and R. Rosenfield. 1.997. Statistical language modelling using the CMU-cambridge toolkit. In: Proc. Eurospeech' 97, Vol. 5, pp. 2707-2710.
7. Conklin, D. 2002. Representation and Discovery of Vertical Patterns in Music, Vol. 2445, Lecture Notes in Artificial Intelligence. London: Springer-Verlag.
8. Cope, D. 1996. Experiments in Musical Intelligence. Madison, WI: A.-R. Editions.
9. Cruz, P. P. 2004. Técnicas de Reconocimiento de Formas Para el Modelado de Estilos Musicales. PhD thesis, Universidad Politécnica de Valencia, Spain.
10. Cruz, P. P. and E. Vidal. 1998. Learning Regular Grammars to Model Musical Style: Comparing Different Coding Schemes, Vol. 1433, Lecture Notes in Artificial Intelligence 1433, Subseries of Lecture Notes in Computer Science, pp. 211-222. New York: Springer-Verlag.
11. Cruz, P. P. and E. Vidal. 2003. Modeling musical style using grammatical inference techniques: A tool for classifying and generating melodies. In: Proc. 3rd International Conference on Web Delivering of Music (WEDELMUSIC 2003), eds. N. Kia, C. Busch, and P. Nesi, pp. 77-84. Leeds, UK: IEEE Computer Society.
12. Cruz, P. P. and E. Vidal. 2005. Grammatical inference applications in music processing. In: Proc. Workshop on Grammatical Inference Applications: Successes and Future Challenges (W10: GIASFC), eds. C. de la Higuera, T. Oates, G. Paliouras, and M. V. Zaanen, 9th International Joint Conference on Artificial Intelligence (IJCAI-05), pp. 39-45. Edinburgh, UK: Edinburgh University.
13. Cruz, P. P., E. Vidal, and J. C. Pérez. 2003. Musical Style Identification Using Grammatical Inference: The Encoding Problem, Vol. 2905, Lecture Notes in Computer Science, pp. 375-382. New York: Springer-Verlag.
14. de la Higuera, C., F. Piat, and F. Tantini (2005). Learning stochastic finite automata for musical style recognition. In Conference on implementation and Application of Automata (CIAA 2005), pp. 345-346.
15. de León, P. P. and J. Iñesta. 2004. Musical style classification from symbolic data: A two-styles case study. Lecture Notes in Computer Science 2771:166-177.
16. Doraisamy, S. and S. Rüger. 2003. Robust polyphonic music retrieval with n-grams. Journal of Intelligent Information Systems 21:53-70.
17. Forney, G. D. 1973. The viterbi algorithm. In Proc. of the IEEE, pp. 268-278.
18. Fu, K. S. 1982. Syntactic Pattern Recognition and Applications. New York: Prentice Hall.
19. Garcia, P. and E. Vidal. 1990. Inference of k-testable languages in the strict sense and application to syntactic pattern recognition. IEEE Trans. on PAMI 12(9):920-925.
20. Jelinek, F. 1998. Statistical Methods for Speech Recognition. Cambridge, MA: MIT Press.
21. Katz, S. M. 1987, March. Estimation of probabilities from sparse data for language model component of a speech recognizer. IEEE Transactions on Acoustic, Speech and Signal [Processing 35(3):400-401.
22. Laske, O. 1973, January. In search of a generative grammar for music. In: Introduction to a Generative Theory of Music, Sonological Reports. Utrecht, The Netherlands: Institute of Sonology.
23. Lerdhal, F. and R. Jackendoff. 1983. A Generative Theory of Tonal Music. Cambridge, MA: The MIT Press.
24. Oncina, J. and P. Garcia. 1992. Inferring Regular Languages in Polynominal Update Time. Pattern Recognition and Image Analysis. Singapore: World Scientific.
25. Papadopoulous, G. and G. Wiggins. 1999. AI methods for algorithmic composition: A survey, a critical view, and future prospects. In: Proc. Symposium, on Musical Creativity (AISB99), ed. G. Wiggins, Edinburgh, UK: Society for the Study of Artificial Intelligence and Simulation of Behavior.
26. Pérez-Sancho, C., J. Iñesta, and J. Calera-Rubio. 2005, June. A. text categorization, aproach for music style recognition. In: Proc. 2nd Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2005. Vol. 3523, Lectures Notes in Computer Science, Estoril, Portugal, pp. 649-657. New York: Springer-Verlag.
27. Pollastri, E. and G. Simoncelli. 2001. Classification of melodies by composer with hidden markov models. In: Proc. First International Conference on WEB Delivering of Music (WEDELMUSIC'01), pp. 88-95. Washington, DC: IEEE Computer Press.
28. Rey, F. 1999. Un sistema de armonización automática. Master's thesis. Facultad de Informática, Universidad Politécnica de Valencia, Spain.
29. Roads, C. 1985. Grammars as representations for music. In: Foundations of Computer Music, eds. C. Roads and J. Strawn, pp. 403-442. Cambridge, MA: The MIT Press.
30. Rulot, H. and E. vidal. 1987. Modelling (sub) string-length based constraints through a gramatical inference method. In: Pattern Recognition Theory and Applications, Vol. FSO, NATO ASI Series, pp. 451-459. New York: Springer-Verlag.
31. Rumsey, F. 1994. MIDI Systems and Control Oxford, UK: Focal Press.
32. Schwanauer, S. M. and D. A. Levitt. 1993. Machine Models of Music. Cambridge, MA: The MIT Press.
33. Selfridge-Field, E. 1.998, August. Representing musical information for retrieval. In: SIGIR: Exploratory Workshop on Music Information Retrieval. Berkeley, CA: Association for Computing Machinery.
34. Shan, M.-K., F.-F. Kuo, and M.-F. Chen. 2002. Music style mining and classification by melody. In: Proc. IEEE International Conference on Multimedia and Expo, Vol. 1, pp. 97-100.
35. Soltau, H., T. Schultz, M. Westphal, and A. Waibel. 1998. Recognition of music types. In: Proc. International Conference on Acoustics. Speech and Signal Processing (ICASSP 98), Seattle, WA, pp. 1137-1140.
36. Temperley, D. 2001. The Cognition of Basic Music Structures. Cambridge, MA: MIT Press.
37. Thollard, F., P. Dupont, and C. de la Higuera 2000. Probabilistic dfa inference using kullback-leibler divergence and minimality. In: International Conference in Machine learning (ICML-00), pp. 975-982. San Francisco: Morgan Kaufmann Publishers.
38. Todd, P. 1988. A sequential network design for musical applications. In: Proc. 1988 Connectionist Models Summer School, pp. 76-84. San Francisco: Morgan Kaufmann Publishers.
39. van Zaanen, M., R. Bod, and H. Honing 2003, September. A memory-based approach to meter induction. In: Proc. 5th Triermial Conference of the European Society for the Cognitive Sciences of Musk (ESCOM), Hanover, Germany.
40. Vidal, E., F. Casacubierta, and P. Garcia. 1995. Grammatical inference and automatic speech recognition. In: Speech Recognition and Coding: New Advances and Treads, ed. J. A. Rubio, New York: Springer Verlag.
41. Vidal, E. and D. Llorens. 1996. Using knowledge to improve n-gram language modelling through the MGGI methodology. In: Grammatical Inference: Learning Syntax from Sentences. Proc. 3rd ICGI, eds. C. de la Higuera and L. Miclet, Vol. 1147, Lecture Notes in Artificial Intelligence. New York: Springer-Verlag.
42. Vidal, E., F. Thollard, F. Casacuberta, C. de la Higuera, and R. Carrasco. 2005. Probabilistic finite-state machines - Part II. IEEE Transaction on Pattern Analisys and Machine Intelligence 27(7):1025-1039.
43. Wiggins, G. A. 1993. A framework for the evaluation of music representation systems. Computer Music Journal 17(3):31-42.
44. Wiggins, G. A. 1998. Music syntax, and the meaning of "meaning." In: Proc. Symposium on Music and Computers, Corfu, Greece.
45. Winograd, T. 1968. Linguistics and the computer analysis of tonal harmony. Journal of Music Theory, Vol. 12, No. 1, pp. 2-49.
46. Witten, I. T. and T. C. Bell. 1991, July. The zero-frequency problem: Estimating the probabilities of novel events in adaptive text compression. IEEE Transactions on Information Theory 37(4):1085-1094.
47. Zalcstein, Y. 1972. Locally testable languajes. Journal of Computer and System Sciences (JCSS) 6:151-167.