A music stream segregation system based on adaptive multi-agents

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2, Issue , 1997, Pages 1126-1131

  Kashino, Kunio ^a   Murase, Hiroshi ^a  

^a Kashino Diverse Brain Research Laboratory of NTT Communication Science Laboratories   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE MECHANISM; AUDITORY SCENE ANALYSIS; LEAST-SQUARES OPTIMIZATION; MUSIC RECOGNITION; PROPOSED ARCHITECTURES; RECOGNITION ACCURACY; SIGNAL PROCESSING ALGORITHMS; STREAM SEGREGATION;

INVERSE PROBLEMS; SIGNAL PROCESSING;

ARTIFICIAL INTELLIGENCE;

EID: 0343041672     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Bell A. J. and Sejnowski T. J.: An Information-Maximization Approach to Blind Separation and Blind Deconvolution. Neural Computation, vol.7, 1129-1159, 1971.
2. Bregman A. S.: Auditory Scene Analysis. M I T Press, 1990.
3. Brown G. J. and Cooke M.: Perceptual Grouping of Musical Sounds: A Computational Model. J. of New Music Research, 23(1):107-132, 1994.
4. Chafe C, Kashima J., Mont-Reynaud B., and Smith J.: Techniques for Note Identification in Polyphonic Music. In Proc. of the 1985 Intl. Computer Music Conf., pp.399-405, 1985.
5. Ellis D.: Prediction-driven Computational Auditory Scene Analysis. PhD. Thesis, Dept. of Electrical Engineering and Computer Science, M.I.T., 1996.
6. Kashino K., Nakadai K., Kinoshita T., and Tanaka H.: Organization of Hierarchical Perceptual Sounds. In Proc. of the 14th Intl. Joint Conf. Artificial Intelligence, Vol.1, 158-164, 1995.
7. Kashino K., Nakadai K., Kinoshita T., and Tanaka H.: Application of Bayesian Probability Network to Music Scene Analysis. In Working Notes of the Computational Auditory Scene Analysis Workshop, IJCAI-95, pp.32-40, 1995.
8. Kashino K. and Murase H.: Sound Source Identification for Music Based on Melody Extraction. In Working Notes of the Computational Auditory Scene Analysis Workshop, IJCAI-97, 1997.
9. Lesser V., Nawab S. H., Gallastegi I., and Klassner F.: IPUS: An Architecture for Integrated Signal Processing and Signal Interpretation in Complex Environments. In Proc. of the 11th National Conf. on Artificial Intelligence, pp.249-255, 1993.
10. Mitchell O. M. E., Ross C. A., and Yates G. H.: Signal Processing for a Cocktail Party Effect. J. Acoust. Soc. Am., 50(2):656-660, 1971.
11. Mont-Reynaud B.: Problem-Solving Strategies in a Music Transcription System. In Proc. of the Intl. Joint Conf on Artificial Intelligence, pp.916-918, 1985.
12. Nakatani T., Okuno G. H., and Kawabata T.: Residue-Driven Architecture for Computational Auditory Scene Analysis. In Proc. of the 14th Intl. Joint Conf. Artificial Intelligence, Vol.1, 165-172, 1995.
13. Nehorai A. and Porat B.: Adaptive Comb Filtering for Harmonic Signal Enhancement. IEEE Trans, on ASSP, 34(5):1124-1138, 1986.
14. Parsons T. W.: Separation of Speech from Interfering Speech by Means of Harmonic Selection. J. Acoust. Soc. Am., 60(4):911-918, 1976.
15. Pearl J.: Fusion, Propagation, and Structuring in Belief Networks. Artificial Intelligence, 29(3):241-288, 1986.