Application of Discriminative Methods for Isolated Word Recognition

  • Josef G. Bauer
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


This paper describes a Hidden Markov Model based system for automatic recognition of isolated digits over telephone lines. For an LDA based linear feature transformation the classes to discriminate are choosen to be the HMM states. For MCE training this selection of classes is compared to the usage of the lexical words treated as classes. Experiments show that for MCE based reestimation of model parameters the latter choice is more appropriate, although in the case of Maximum Likelihood trainined parameters the correlation between Word Error rate and State Error rate is quite high.


Feature Vector Linear Discriminant Analysis Word Error Rate Minimum Classification Error Linear Discriminant Analysis Class 
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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Josef G. Bauer
    • 1
  1. 1.Siemens AGMunichGermany

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