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2011 | nr 4 | 259-268
Tytuł artykułu

Quality assessment of intonation of choir singers using F0 and trend lines for singing sequence

Warianty tytułu
Języki publikacji
In this paper a part of quality assessment process of the intonation of singing voice is described. Intonation is understood here as the ability to precisely reproduce a given pitch. Such evaluation is typically performed by voice production experts (voice trainers) or other persons associated with singing. For the purpose of determining the quality of intonation an exercise performed by singers on subsequent pitches was proposed in the article. One of pitch extraction methods is used to determine the fundamental frequency and estimate the F0 trajectory. Based on the obtained trajectory, an attempt is made to determine a general trend among tested singers. It is also indicated, that it is possible to point out problems in singing for tested persons, which can be useful in further stages of voice training.

Opis fizyczny
Bibliogr. 12 poz., rys., tab.
  • West Pomeranian University of Technology, Szczecin (Poland), Faculty of Computer Science and Information Technology
  • [1] Dayme M. A., Besterman A., Dynamics of the Singing Voice, Springer, 2009
  • [2] Sundberg J., The Science of the Singing Voice, Northern Illinois University Press., 1989
  • [3] Murry T., Pitch-matching accuracy in singers and nonsingers, J. Voice, 4, 1990, pp. 317–321
  • [4] Brown W., Rothman H., Sapienza C., Perceptual and acoustic study of professional trained versus untrained voices, J. Voice, 3, 2000, pp. 301–309
  • [5] Tomoyasu Nakano, Masataka Goto, Yuzuru Hiraga, An Automatic Singing Skill Evaluation Method for Unknown Melodies Using Pitch Interval Accuracy and Vibrato Features, Interspeech, 2006
  • [6] Żwan P., Kostek B., System for Automatic Singing Voice Recognition, JAES Volume 56 Issue 9, 2008, pp. 710-723
  • [7] Rabiner L., On the Use of Autocorrelation Analysis for Pitch Detection, IEEE Trans. Audio, Speech, Signal Process., vol. 25, 1977, pp. 24–33
  • [8] Dziubinski M., Kostek B., Octave Error Immune and Instantaneous Pitch Detection Algorithm, J. New Music Res., vol. 34, 2005, pp. 273–292
  • [9] Szczerba M., Czyzewski A., Pitch Detection Enhancement Employing Music Prediction, J. Intell. Inform. Sys., vol. 24, no. 2–3, 2005, pp. 223–251
  • [10] Kostek B., Szczuko P., Zwan P., Dalka P., Processing of Musical Data Employing Rough Sets and Artificial Neural Networks, in Trans. on Rough Sets, Springer, Berlin, Heidelberg, New York, 2005, pp. 112–133.
  • [11] de Cheveigné A., Kawahara H., YIN, a fundamental frequency estimator for speech and music, J. Acoust. Soc. Am. Volume 111, Issue 4, 2002, pp. 1917-1930
  • [12] D. Larose, Data Mining Methods and Models, John Wiley & Sons, Inc., 2006
Typ dokumentu
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