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Speaker identification using hybrid Karhunen–Loeve transform and Gaussian mixture model approach

Authors
Journal
Pattern Recognition
0031-3203
Publisher
Elsevier
Publication Date
Volume
37
Issue
5
Identifiers
DOI: 10.1016/j.patcog.2003.08.013
Keywords
  • Karhunen–Loeve Transform
  • Bhattacharyya Distance
  • Gaussian Mixture Models
  • Speaker Identification
  • Mel Frequency Cepstral Coefficients
Disciplines
  • Computer Science

Abstract

Abstract This paper proposes a classification scheme that incorporates Karhunen–Loeve transform (KLT) and Gaussian mixture model (GMM) for text-independent speaker identification. Our results show that the combination is beneficial to both classification accuracy and computational cost. For a database with 500 Mandarin speakers, it is demonstrated that accuracy improvement of up to 4% and computational cost saving of 10 times compared to those of the conventional GMM model can be achieved.

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