Feature selection using genetics-based algorithm and its application to speaker identification


Demirekler M., Haydar A.

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 99), Arizona, United States Of America, 15 - 19 March 1999, pp.329-332 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icassp.1999.758129
  • City: Arizona
  • Country: United States Of America
  • Page Numbers: pp.329-332
  • Middle East Technical University Affiliated: Yes

Abstract

This paper introduces the use of genetics-based algorithm in the reduction of 24 parameter set (i.e the base set) to a 5,6,7,8 or 10 parameter set, for each speaker in text-independent speaker identification. The feature selection is done by finding the best features that discriminates a person from his/her two closest neighbors. The experimental results show that there is approximately 5% increase in the recognition rate when the reduced set of parameters are used. Also the amount of calculation necessary for speaker recognition using the reduced set of features is much less than the amount of calculation required using the complete feature set in the testing phase. Hence it is more desirable to use the subset of the complete feature set found using the genetic algorithm suggested.