International Conference on Speech and Computer

SPECOM 2015: Speech and Computer pp 389-396

Speaker Identification Using Semi-supervised Learning

  • Nikos Fazakis
  • Stamatis Karlos
  • Sotiris Kotsiantis
  • Kyriakos Sgarbas
Conference paper

DOI: 10.1007/978-3-319-23132-7_48

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9319)
Cite this paper as:
Fazakis N., Karlos S., Kotsiantis S., Sgarbas K. (2015) Speaker Identification Using Semi-supervised Learning. In: Ronzhin A., Potapova R., Fakotakis N. (eds) Speech and Computer. SPECOM 2015. Lecture Notes in Computer Science, vol 9319. Springer, Cham

Abstract

Semi-supervised classification methods use available unlabeled data, along with a small set of labeled examples, to increase the classification accuracy in comparison with training a supervised method using only the labeled data. In this work, a new semi-supervised method for speaker identification is presented. We present a comparison with other well-known semi-supervised and supervised classification methods on benchmark datasets and verify that the presented technique exhibits better accuracy in most cases.

Keywords

Semi-supervised learning Speaker identification Classification using labeled Unlabeled data 

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nikos Fazakis
    • 1
  • Stamatis Karlos
    • 1
  • Sotiris Kotsiantis
    • 1
  • Kyriakos Sgarbas
    • 1
  1. 1.University of PatrasPatrasGreece

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