Voice intensity based gender classification by using Simpson's rule with SVM

Mansour Alsulaiman, Zulfiqar Ali, Ghulam Muhammad

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

The proposed technique measures the voice intensity of an utterance by calculating area under the curve. The curve is obtained by normalizing the cubic polynomial fitted through the peaks. These peaks are found from each frame of the utterance when it is divided into segments of 20 milliseconds. The Simpson's rule is used to calculate area under the curve and SVM uses this area to classify the genders. The use of one dimensional feature, area of utterance, is an evidence for the time and computational efficiency of this technique. The aspects observed in this paper, for the validity of the technique, are: it works for different natural languages, independent of recording equipment, any text can be used for the classification, and its biasness when different number of male and female speakers are used for the training of the system. A promising classification rate of 98.27% is achieved.

Original languageEnglish
Pages552-555
Number of pages4
Publication statusPublished - 1 Jun 2012
Event2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012 - Vienna, Austria
Duration: 11 Apr 201213 Apr 2012

Conference

Conference2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012
CountryAustria
CityVienna
Period11/04/1213/04/12

Keywords

  • Area under the curve
  • Simpson's Rule
  • SVM
  • TIMIT
  • Voice Intensity

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    Alsulaiman, M., Ali, Z., & Muhammad, G. (2012). Voice intensity based gender classification by using Simpson's rule with SVM. 552-555. Paper presented at 2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012, Vienna, Austria.