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JACIII Vol.11 No.5 pp. 464-468
doi: 10.20965/jaciii.2007.p0464
(2007)

Paper:

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Key Characteristics of Hymns

Tatsuo Kamitani* and Minoru Matsuda**

*School of Management and Business Administration, Kyoto Sosei University, Fukuchiyama, Kyoto 620-0886, Japan

**Graduate School of Engineering, Osaka Electro-Communication University, Neyagawa, Osaka 572-8530, Japan

Received:
September 19, 2006
Accepted:
February 23, 2007
Published:
June 20, 2007
Creative Commons License
Keywords:
key finding, bar patterning, hymn, EM algorithm
Abstract
The authors propose a way of patterning the bars of monophonic melodies in hymns and finding keys from such patterns. The authors represent monophonic melody bars on a vector showing the duration of pitch chroma contained in each bar. In experiments, the authors patterned bars of 352 four/four beat hymns, defined the distance between the bar key and melody, and found they key from this, correctly 83.1% of the time. The authors also propose a way to determine the maximum likelihood of a contaminated normal distribution of distance between patterns using an EM algorithm. Key characteristics of hymns were then studied using this method.
Cite this article as:
T. Kamitani and M. Matsuda, “Key Characteristics of Hymns,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.5, pp. 464-468, 2007.
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References
  1. [1] D. Deutcsh (Ed.), “The psychology of music,” Academic Press, San Diego, 1982.
  2. [2] C. L. Krumhansl and E. J. Kessler, “Tracing the dynamic changes in perceived tonal organization in a spatial representation of music keys,” Psychol. Rev., Vol.89, pp. 334-368, 1982.
  3. [3] K. Akiyama, M. Matsuda, and M. Nakano, “The discrimination of tonality in Japanese popular songs – Feature vector and the entropy of pitch transition,” The Journal of the Acoustical Society of Japan, Vol.44, No.11, pp. 809-814, 1988.
  4. [4] C. L. Krumhansl, “A key finding algorithm based on tonal hierarchies in Cognitive foundations of musical pitch,” Oxford University Press, New York, pp. 77-110, 1990.
  5. [5] M. Matsuda and K. Akiyama, “Tonality discrimination and tonic identification from melodic motion of monodies,” The Journal of the Acoustical Society of Japan, Vol.52, No.4, pp. 253-260, 1996.
  6. [6] T. Winograd, “Linguistics and the computer analysis of tonal harmony,” J. Music Theory, Vol.12, pp. 2-49, 1968.
  7. [7] M. Matsuda and K. Akiyama, “Japanese favorite song and its tonality,” Proc. JCMMA 94, pp. 86-91, 1994.
  8. [8] J. E. Youngblood, “Style as information,” Journal of Music Therapy, Vol.2, pp. 24-35, 1958.
  9. [9] J. F. P. Brooks and J. P. G. Hopkins, “An Experiment in Musical Composition,” IRE Transactions on Computers, EC-6, pp. 175-182, 1957.
  10. [10] A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” Journal of Royal Statist Soc, Ser B, Vol.39, pp. 1-38, 1977.

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