Polyphonic audio key finding using the spiral array CEG algorithm

IEEE International Conference on Multimedia and Expo, ICME 2005

Volumn 2005, Issue , 2005, Pages 21-24

  Chuan, Ching Hua ^a   Chew, Elaine ^a  

^a University of Southern California ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

KRUMHANSL SCHMUCKLER (K-S) PROBE; MOZART'S SYMPHONIES; PITCH STRENGTH INFORMATION; POLYPHONIC AUDIO;

ALGORITHMS; FAST FOURIER TRANSFORMS; FEATURE EXTRACTION; INDEXING (OF INFORMATION);

CONTENT BASED RETRIEVAL;

EID: 33750539514     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICME.2005.1521350     Document Type: Conference Paper

References (21)

1. th International Conference on Music Information Retrieval.
2. Chew, E. (2000). Towards a Mathematical Model of Tonality. Doctoral dissertation, Department of Operations Research, Massachusetts Institute of Technology, Cambridge, MA.
3. Chew, E. (2001). Modeling Tonality: Applications to Music Cognition. Proceedings of the 23rd Annual Conference of the Cognitive Science Society, Edinburgh, Scotland.
4. Chew, E. and Chen, Y. C. (2003). Mapping MIDI to the Spiral Array: Disambiguating Pitch Spellings. H. K. Bhargava and Nong Ye (Eds.), Computational Modeling and Problem Solving in the Networked World, Kluwer, pp.259-275. Proceedings of the 8th INFORMS Computer Society Conference, ICS2003, Chandler, AZ, Jan 8-10, 2003.
5. Chew, E. and Chen, Y. C. (2005). Real-Time Pitch Spelling Using the Spiral Array. Computer Music Journal. 29:2, Summer 2005.
6. Chew, E. and François, A. R. J. (2003). MuSA.RT - Music on the Spiral Array. Real-Time. In Proceedings of the ACM Multimedia '03 Conference, MM'03, Berkeley, CA, Nov 2-8, 2003.
7. Cook, Perry R. (2001). Music, Cognition, and Computerized Sound: An Introduction to Psychoacoustics. MIT Press.
8. Dziubinski M. and Kostek B. (2004). High Accuracy and Octave Error Immune Pitch Detection Algorithms. Archives of Acoustics.
9. th International Conference on Music Information Retrieval.
10. Krumhansl, C.L. (1990). Quantifying Tonal Hierarchies and Key Distances. Cognitive Foundations of Musical Pitch, chapter 2, 16-49.
11. Longuet-Higgines, H.C., Steedman, M.J. (1971). On Interpreting Bach. Machine Intelligence, vol. 6, 221-241.
12. nd Edition. McGraw-Hill
13. Noll, A.M. and Schroeder, M.R. (1964) Short-time Cepstrum Pitch Detection. Journal of the Acoustical Society of America, vol 36, pp 1030.
14. th International Conference on Music Information Retrieval.
15. Rabiner and Gold (1975). Theory and Applications of Digital Signal Processing. IEEE Transactions on Acoustics, Speech, and Signal Processing AU-20; 322-337.
16. Schroeder, M.R. (1968). Period Histogram and Product Spectrum: New Methods for Fundamental-Frequency Measurement. Journal of the Acoustical Society of America, vol. 43, pp. 829-834.
17. Szczerba, M. and Czyzewski, A. (2002). Pitch Estimation Enhancement Employing Neural Network-Based Music Prediction. Proc. IASTED Intern. Conference, Artificial Intelligence and Soft Computing, 413-418, 17.7.2002-19.7.2002, Banff, Canada.
18. Temperley, D. (1999). What's Key for Key? The Kwmhansl-Schmuckler Key-Finding Algorithm Reconsidered. Music Perception, 17(1), 65-100.
19. Tolonen, T. and Karjalainen, M. (2000), A Computationally Efficient Multipitch Analysis Model. IEEE Trans. On Speech and Audio Processing, 8(6): 708-716.
20. Tzanetakis, G. Ermolinskyi, A. and Cook, P. (2003). Pitch Histograms in Audio and Symbolic Music Information Retrieval. Journal of New Music Research, 32(2), 143-152.
21. International Organization for Standardization, Acoustics - Standard Turing Frequency (Standard Musical Pitch), ISO 16:1975.