A minimax classification approach with application to robust speech recognition

  title={A minimax classification approach with application to robust speech recognition},
  author={Neri Merhav and Chin-Hui Lee},
  journal={IEEE Trans. Speech and Audio Processing},
AbstructA minimax approach for robust classification of parametric information sources is studied and applied to isolatedword speech recognition based on hidden Markov modeling. The goal is to reduce the sensitivity of speech recognition systems to a possible mismatch between the training and testing conditions. To this end, a generalized likelihood ratio test is developed and shown to be optimal in the sense of achieving the highest asymptotic exponential rate of decay of the error probability… CONTINUE READING
Highly Cited
This paper has 70 citations. REVIEW CITATIONS
42 Citations
46 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 42 extracted citations

71 Citations

Citations per Year
Semantic Scholar estimates that this publication has 71 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 46 references

Hidden Markov modeling using a dominant sequence of states with application to speech recognition,

  • N. Merhav, Y. Ephraim
  • Computer, Speech and Language,
  • 1991

Estimation using log spectral distance criterion and Markov models for recognition of noisy speech

  • M. Weintraub
  • Proc . IEEE Int . Con $ Acoust . . Speech…
  • 1990

Noise compensation for speech recognition using probabilistic models

  • N. C. Sedgwick
  • Proc . IEEE Int . Con $ Acoust . . Speech…
  • 1990

Probabilistic vector mapping of noisy speech parameters for HMM word spotting,

  • H. Gish, Y.-L. Chow, R. Rohlicek
  • in Proc. IEEE Int. Con$ Acoust., Speech, Signal…
  • 1990


  • Jan.
  • 112. Y. Ephraim, A. Dembo, and L. R. Rabiner, “A…
  • 1990

Similar Papers

Loading similar papers…