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A Novel System for Music Learning using Low Complexity Algorithms
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 6 - Number 4 |
| Year of Publication: 2013 |
| Authors: Amr Hesham, Ann Nosseir, Omar H. Karam |
10.5120/ijais13-451042
|
Amr Hesham, Ann Nosseir, Omar H. Karam . A Novel System for Music Learning using Low Complexity Algorithms. International Journal of Applied Information Systems. 6, 4 ( October 2013), 22-29. DOI=10.5120/ijais13-451042
Abstract
This paper introduces a music learning system that uses new low complexity algorithms and aims to solve the four most common problems faced by self-learning beginner pianists: reading music sheets, playing fast tempo music pieces, verifying the key of a music piece, and finally evaluating their own performances. In order to achieve these aims, the system proposes a monophonic automatic music transcription system capable of detecting notes in the range from G2 to G6. It uses an autocorrelation algorithm along with a binary search based algorithm in order to map the detected frequencies of the individual notes of a musical piece to the nearest musical frequencies. To enable playing fast music, the system uses a MIDI player equipped with a virtual piano as well as section looping and speed manipulation functionalities to enable the user to start learning a musical piece slowly and build up speed. Furthermore, it applies the Krumhansl-Schmuckler key-finding algorithm along with the correlation algorithm to identify the key of a musical piece. A musical performance evaluation algorithm is also introduced which compares the original performance with that of the learner's producing a quantitative similarity measure between the two. The experimental evaluation shows that the system is capable of detecting notes in the range from G2 to G6 with an accuracy of 88. 7% in addition to identifying the key of a musical piece with an accuracy of 97. 1%.
References
- Klapuri , A. & Virtanen , T. , (2009), " Automatic music transcription," In Havelock, D. , Kuwano, S. , & Vorländer, M. Handbook of signal processing in acoustics, Springer New York, NY, Vol. IV, pp. 277-303.
- Good, M. (2001), "Musicxml: An internet-friendly format for sheet music", XML Conference and Expo, Montvale, NJ, February 2001, pp. 3-4.
- Scogin, N. (2010), Barron's AP music theory, Barron's Educational Series. N. Y.
- Brandao, M. , Wiggins, G. , & Pain, H. (1999) "Computers in music education," In Geraint Wiggins, AISB'99 Symposium on Musical Creativity, pp. 82-88.
- Burns, H. L. , & Capps, C. G. (1988), Foundations of intelligent tutoring systems: An introduction, In Polson, M. C. & Richardson, J. J. , Foundations of intelligent tutoring systems, Hillsdale: Lawrence Erlbaum Associates, pp. 1-19.
- Scheirer, E. D. (1995), "Extracting expressive performance information from recorded music", Master's thesis, Massachusetts Institute of Technology, Media Laboratory
- Moore, F. R. (1990), Elements of computer music, Prentice-Hall, Inc. , NY
- Bello, J. P. , Monti, G. , & Sandler, M. (2000), "Techniques for automatic music transcription", In the First International Symposium on Music Information Retrieval ISMIR-00, Plymouth, Massachusetts, USA. October 2000, pp. 23-25.
- Costantini, G. , Todisco, M. , Perfetti, R. , Basili, R. , & Casali, D. (2010), "Memory Based Automatic Music Transcription System for Percussive Pitched Instruments", In 1st International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC), Orlando, Florida, USA, April 2010
- Benetos, E. , & Dixon, S. (2011), "Multiple-F0 Estimation and Note Tracking for using a convolutive probabilistic model". Music Information Retrieval Evaluation eXchange, Miami, Florida, USA, October 2011.
- Benetos, E. , Klapuri, A. , & Dixon, S. (2012), "Score-informed transcription for automatic piano tutoring", IEEE Signal Processing Conference (EUSIPCO), Bucharest, August 2012, pp. 2153-2157
- Guo, Y. , & Tang, J. (2012), "A Combined Mathematical Treatment for a Special Automatic Music Transcription System", Abstract and Applied Analysis, December, Vol. 2012, pp. 13
- Hasegawa, B. H. (1987), "The physics of medical x-ray imaging. Medical Physics Pub Corp; June, ed. 2.
- Middleton, G. (2003). Pitch Detection Algorithms. Retrieved from the Connexions Web site: http://cnx. org/content/m11714/1. 2/
- Temperley, D. (1999). "What's key for key? The Krumhansl-Schmuckler key-finding algorithm reconsidered". Music Perception, Vol. 17, pp. 65-100.
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