Pitch detection enhancement employing music prediction

Journal of Intelligent Information Systems

Volumn 24, Issue 2-3, 2005, Pages 223-251

  Szczerba, Marek ^a   Czyzewski, Andrzej ^a  

^a GDANSK UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Music prediction; Musical pitch; Neural networks; Pitch detection

Indexed keywords

ALGORITHMS; COMPUTER MUSIC; ERROR ANALYSIS; ESTIMATION; KNOWLEDGE ENGINEERING; NEURAL NETWORKS;

AUDIO SIGNAL PROCESSING; MUSIC PREDICTION; MUSICAL PITCH; SIGNAL SEGMENTATION;

SIGNAL DETECTION;

EID: 17444403978     PISSN: 09259902     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10844-005-0324-6     Document Type: Article

References (30)

1. Beauchamp, J.W., Maher, R.C., and Brown, R. (1993). Detection of Musical Pitch from Recorded Solo Performances. 94th Audio Eng. Soc. Convention, Preprint 3541, Berlin, March 16-19.
2. Brown, J.C. (1992). Musical Fundamental Frequency Tracking Using a Pattern Recognition Method. J. Acoust. Soc. Am. 92(3), 1394-1402.
3. de Cheveigné, A. and Kawahara, H. (2002). YIN, a Fundamental Frequency Estimator for Speech and Music. J. Acoust. Soc.Am., 111(4), 1917-1930.
4. Cook, P.R., Morill, D., and Smith, J.O. (1998). An Automatic Pitch Detection and MIDI Control System for Brass Instruments. J. Acoust. Soc. Am, 92(4 pt 2), 2429-2430.
5. Czyzewski, A., Szczerba, M., and Kostek, B. (2004). Musical Phrase Representation and Recognition by Means of Neural Networks and Rough Sets. In J.W. Grzymala-Busse, B. Kostek, R.W. Swiniarski, and M. Szczuka, (Eds.), Transactions on Rough Sets, pp. 259-284.
6. Gelfand, S.A. (1998). Hearing: An Introduction to Psychological and Psychological Acoustics. New York: Marcel Dekker, Inc.
7. Herrera, P., Amatriain, X., Battle, E., and Serra, X. (2000). Towards Instrument Segmentation for Music Content Description: A Critical Review of Instrument Classification Techniques. In Proc. Intern. Symposium on Music Information Retrieval, Indiana, USA.
8. Hess, W. (1983). Pitch Determination of Speech Signals: Algorithms and Devices. Springer Berlin: Verlag, Tokyo: Heidelberg, New York.
9. Hörnel, D. (1997). MELONET I: Neural Nets for Inventing Baroque-Style Chorale Variations. In M.I. Jordan, M.J. Kearns, and S.A. Solla (Eds.), Advances in Neural Information Processing 10 (NIPS 10), MIT Press.
10. Klapuri, A. (1999). Wide-band Pitch Estimation for Natural Sound Sources with Inharmonicities. 106th Audio Eng. Soc. Convention, Preprint 4906, Munich, May 8-11.
11. Kostek, B. (1999). Soft Computing in Acoustics, Applications of Neural Networks, Fuzzy Logic and Rough Sets to Musical Acoustics. Studies in Fuzziness and Soft Computing, New York: Physica Verlag, Heidelberg.
12. Kostek, B. and Czyzewski, A. (2001). Representing Musical Instrument Sounds for Their Automatic Classification. J. Audio Eng. Soc., 49(9), 768-785.
13. Maher, R.C. and Beauchamp, J.W. (1974). Fundamental Frequency Estimation of Musical Signals Using a Two-Way Mismatch Procedure. J. Acoust. Soc. Am., 95(4), 2254-2263.
14. McAulay, R.J., and Quatieri, T.F. (1995). In W. B. Kleijn & K.K. Paliwal (Eds.) Sinusoidal Coding, Speech Coding and Synthesis. Elsevier Science B.V., pp. 121-131.
15. Meddis, R. and Hewitt M.J. (1991). Virtual Pitch and Phase Sensitivity of a Computer Model of the Auditory Periphery. I: Pitch Identification. J. Acoust. Soc. Am., 89(6), 2866-2881.
16. Moorer, J.A. (1974). The Optimum Comb Method of Pitch Period Analysis of Continuous Digitized Speech. IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-22, 5, 330-338.
17. Moradi, H., Gizymala-Busse, J.W., and Roberts, J.A. (1998). Entropy of English Text: Experiments with Humans and a Machine Learning System Based on Rough Sets. Information Sciences, 104(1/2), 31-47.
18. Mozer, M.C. (1991). IN Todd, P. M. and Loy, D.G. (Eds.), Connectionist Music Composition Based on Melodic, Stylistic, and Psychophysical Constraints, Music and Connectionism Cambridge, Massachusetts, London, England: The MIT Press, pp. 195-211.
19. Noll, A.M. (1964). Short-Time Spectrum And 'Cepstrum' Techniques For Vocal-Pitch Detection. J. Acoust. Soc. Am., 36, 296-302.
20. Paganini (1990). N., 24 Capricci op. 1, Alexander Markov, CD, Erato 2292-45502-2.
21. Rabiner, L., Cheng, M.J., Rosenberg, A.E., and Gonegal, C.A. (1976). A Comparative Performance Study of Several Pitch Detection Algorithms. Transactions on Acoustics, Speech, and Signal Processing, ASSP-24, 399-418.
22. Rife, D.C. and Boorstyn R.R. (1974). Single-Tone Parameter Estimation from Discrete-Time Observations. IEEE Transactions on Information Theory, 20(5), 591-598.
23. Rife, D.C. and Boorstyn, R.R. (1976). Multiple Tone Parameter Estimation from Discrete-Time Observations. Bell System Technical Journal, 55(3), 1389-1410.
24. Ross, M.J., Shaffer, H.L., Cohen, A., Freudberg, R., and Manley, H.J. (1974). Average Magnitude Difference Function Pitch Extractor. IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-2, (5), 353-362.
25. Schroeder, M.R. (1968). Period Histogram and Product Spectrum: New Methods for Fundamental Frequency Measurement. J. Acoust. Soc. Am., 43, 829-834.
26. Szczerba, M. (1999). Recognition and Prediction of Music: A Machine Learning Approach. 106th AES Convention, Munich, May 8-11, Preprint 4904.
27. Telemann, G.Ph. (1984). Twelve Fantasies for Oboe Solo, Heinz Holliger, CD, Nippon Columbia, Denon, 38C37-7089.
28. Todd, P.M. (1991). In Todd, P. M. and Loy, D.G. (Eds.), A Connectionist Approach to Algorithmic Composition, Music and Connectionism, Cambridge, Massachusetts, London, England: The MIT Press, pp. 173-194.
29. Walmsley, P.J., Godsill S.J., and Rayner, P.J.W. (1999). Polyphonic Pitch Tracking Using Joint Bayesian Estimation of Multiple Frame Parameters. In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 17th-20th October: New Paltz (NY).
30. Zell, A. (1995). u.a., SNNS - Stuttgart Neural Network Simulator User Manual, Ver. 4.1.