Abstract
In the continuing investigation of the relationship between music and emotions it is recognized that MPEG-7 based MIR systems are the state-of-the-art. Also, it is known that non-temporal systems are diametrically unconducive to pitch analysis, an imperative for key and scalar analysis which determine emotions in music. Furthermore, even in a temporal MIR system one can only find the key if the scale is known or vice-versa, one can only find the scale if the key is known. We introduce a new MIRAI-based decision-support system that, given a blind database of music files, can successfully search for both the scale and the key of an unknown song in a music database and accordingly link each song to its set of scales and possible emotional states.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Chew, E.: Music information processing: a new application for operations researchers. Bulletin of AIROnews 7(3), 9–14 (2002)
Hevner, K.: Experimental studies of the elements of expression in music. American Journal of Psychology 48, 246–268 (1936)
Lewis, R., Zhang, X., Raś, Z.: Knowledge discovery based identification of musical pitches and instruments in polyphonic sounds. International Journal of Engineering Applications of Artificial Intelligence 20(5), 637–645 (2007)
Lewis, R., Raś, Z.: Rules for processing and manipulating scalar music theory. In: Proceedings of MUE 2007, IEEE Conference, Seoul, Korea, pp. 26–28 (2007)
Lewis, R., Wieczorkowska, A.: A Categorization of musical instrument sounds based on numerical parameters. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 784–792. Springer, Heidelberg (2007)
Li, T., Ogihara, M.: Detecting emotion in music, in ISMIR 2003 Proceed (2003), http://ismir2003.ismir.net/papers/Li.PDF
McClellan, R.: The healing forces of music. In: Element Inc., Rockport, MA (1966)
Pawlak, Z.: Information systems - theoretical foundations. Information Systems Journal 6, 205–218 (1991)
Raś, Z., Zhang, X., Lewis, R.: MIRAI: Multi-hierarchical, FS-tree based music information retrieval system. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 28–30. Springer, Heidelberg (2007)
Sevgen, A.: The science of musical sound. Scientific American Books Inc., New York (1983)
Sloboda, J.A., ONeill, S.A.: Emotions in everyday listening to music. In: Juslin, P.N., Sloboda, J.A. (eds.) Music and Emotion: Theory and Research, pp. 415–430. Oxford Univ. Press, Oxford (2001)
Valentinuzzi, M.E., Arias, N.E.: Human psychophysiological perception of musical scales and nontraditional music. IEEE/Eng Medicine and Biol. Mag. 18(2), 54–60 (1999)
Vink, A.: Music and Emotion, living apart together: a relationship between music psychology and music therapy. Nordic Journal of Music Therapy 10(2), 144–158 (2001)
Wieczorkowska, A., Synak, P., Lewis, R., Raś, Z.: Creating reliable database for experiments on extracting emotions from music. In: IIPWM 2005 Proceedings. Advances in Soft Computing, pp. 395–402. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lewis, R.A., Jiang, W., Raś, Z.W. (2008). Mining Scalar Representations in a Non-tagged Music Database. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds) Foundations of Intelligent Systems. ISMIS 2008. Lecture Notes in Computer Science(), vol 4994. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68123-6_48
Download citation
DOI: https://doi.org/10.1007/978-3-540-68123-6_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68122-9
Online ISBN: 978-3-540-68123-6
eBook Packages: Computer ScienceComputer Science (R0)