Improvgenerator: Online grammatical induction for on-the-fly improvisation accompaniment

Proceedings of the International Conference on New Interfaces for Musical Expression

Volumn , Issue , 2010, Pages 469-472

  Kitani, Kris M ^a   Koike, Hideki ^a  

^a UNIVERSITY OF ELECTRO COMMUNICATIONS   (Japan)

Author keywords

Algorithmic Composition; Grammatical Induction; Machine Improvisation; Stochastic Context Free Grammars

Indexed keywords

CONTEXT FREE GRAMMARS; MUSIC;

'CURRENT; ALGORITHMIC COMPOSITIONS; GENERATIVE ALGORITHMS; GRAMMATICAL INDUCTION; IMPROVIZATION; MACHINE IMPROVISATIONS; MUSICAL EXPRESSION; PERFORMANCE; REAL- TIME; STOCHASTIC CONTEXT FREE GRAMMAR;

STOCHASTIC SYSTEMS;

EID: 84919920603     PISSN: 22204792     EISSN: 22204806     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. G. Assayag, G. Bloch, M. Chemillier, A. Cont, and S. Dubnov. OMax brothers: a dynamic topology of agents for improvization learning. In Proceedings of the 1st ACM workshop on Audio and music computing multimedia, page 132. ACM, 2006.
2. G. Assayag and S. Dubnov. Using factor oracles for machine improvisation. Soft Computing-A Fusion of Foundations, Methodologies and Applications, 8(9):604–610, 2004.
3. R. M. Keller and D. R. Morrison. A grammatical approach to automatic improvisation. In Proceedings of the Sound and Music Computing Conference, pages 330–337, 2007.
4. J. Kippen and B. Bel. Modeling music with grammars: Formal language representation in the Bol processor. In Computer Representations and Models in Music, pages 207–238, 1988.
5. K. M. Kitani, Y. Sato, and A. Sugimoto. Recovering the basic structure of human activities from noisy video-based symbol strings. International Journal of Pattern Recognition and Artificial Intelligence, 22(8):1621–1646, 2008.
6. G. Lewis. Too many notes: Computers, complexity and culture in voyager. Leonardo Music Journal, pages 33–39, 2000.
7. P. Mavromatis and M. Brown. Parsing context-free grammars for music: A computational model of Schenkerian analysis. In Proceedings of the International Conference on Music Perception and Cognition, pages 414–415, 2004.
8. J. McCormack. Grammar based music composition. Complex Systems 96: From Local Interactions to Global Phenomena, 3:320–336, 1996.
9. C. G. Nevill-Manning and I. H. Witten. Identifying hierarchical structure in sequences: A linear-time algorithm. Journal of Artificial Intelligence Research, 7:67, 1997.
10. D. V. Pynadath and M. P. Wellman. Generalized queries on probabilistic context-free grammars. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20:1285–1290, 1996.
11. Y. Sakakibara, M. Brown, R. C. Underwood, I. S. Mian, and D. Haussler. Stochastic context-free grammars for modeling RNA, 1993.
12. B. Thom. Learning models for interactive melodic improvisation. In Proceedings of the International Computer Music Conference, pages 190–193, 1999.
13. G. Wang and P. Cook. ChucK: A programming language for on-the-fly, real-time audio synthesis and multimedia. In Proceedings of the 12th annual ACM international conference on Multimedia, pages 812–815, New York, NY, USA, 2004. ACM.
14. G. Weinberg, A. Raman, and T. Mallikarjuna. Interactive jamming with Shimon: a social robotic musician. In Proceedings of the 4th ACM/IEEE international conference on Human robot interaction, pages 233–234. ACM, 2009.
15. N. J. Zabusky. Computational synergetics: visualization and vortex dynamics. Journal of Computational and Applied Mathematics, 22(2-3):285–295, 1988.