Towards a Small Intra-Speaker Variability Models

  • I. D. Jokic University of Novi Sad
  • S. D. Jokic University of Novi Sad
  • V. D. Delic University of Novi Sad
  • Z. H. Peric University of Nis
Keywords: Automatic speaker recognition, mel frequency cepstral coefficients, intra-speaker variability, distinction matrix, weight matrix

Abstract

Automatic speaker recognizer used in experiments described in this paper uses vectors of mel-frequency cepstral coefficients as feature vectors and covariance matrices for speakers modelling. By comparing the models of training and test speech of the same speakers it was noticed significant differences in some model elements. Speaker models had inherent intra-speaker variability. In the observed test the distinction matrix was introduced as the measure of intra-speaker variability of all speaker models in available speech database. Based on the values of elements in distinction matrix, the ranges of validity of elements in weighting matrix were established. Each element in covariance matrix of a speaker was pondered by appropriate weighting coefficient. Application of this transformation resulted in higher accuracy of automatic speaker recognition.

DOI: http://dx.doi.org/10.5755/j01.eee.20.6.7276

Published
2014-06-09
Section
SIGNAL TECHNOLOGY