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A Boosting Approach for Utterance Verification

  • Chengyu Dong
  • Yuan Dong
  • Dezhi Huang
  • Jun Guo
  • Haila Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

Utterance verification is a process, in which a spoken utterance is verified against the given keyword. This process is used to make a decision on acceptance or rejection. In this paper, we propose a new approach to the utterance verification, using a boosting classifier with ten confidence measures. This classifier combines a set of ’weak’ learners into a ’strong’ one. The experimental results present that it can remarkably improve the verification performance. Compared with a single confidence measure, the equal error rate is reduced by up to 23%. The results also show that the boosting classifier is better than the SVM and MLP classifiers, in term of the equal error rate.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chengyu Dong
    • 1
  • Yuan Dong
    • 1
    • 2
  • Dezhi Huang
    • 2
  • Jun Guo
    • 1
  • Haila Wang
    • 2
  1. 1.School of Information Engineering, Beijing University of Posts and Telecommunications, 100876China
  2. 2.France Telecom R&D Beijing Co, Ltd., 2 Science Institute South Road,Haidian District, Beijing, 100080China

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