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On the Use of the Leaving-One-Out Method in Statistical Language Modelling

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Part of the book series: NATO ASI Series ((NATO ASI F,volume 147))

Abstract

The probability estimates in stochastic language modelling often depend on some additional parameters apart from the training data. These parameters are typically related to the probabilities of events not seen in the training data and conventional maximum-likelihood methods therefore fail to determine them. We present a special form of cross validation, the leaving-one-out concept, to solve this problem. The application of this technique to several different modelling approaches reveals its flexibility and in some cases the simple way of computation. Experiments, performed on an English corpus of 1.1 million words, show the good generalization capability.

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References

  1. R. O. Duda, P. E. Hart: Pattern Classification and Scene Analysis, Wiley, New York, 1973.

    MATH  Google Scholar 

  2. I J. Good: “The population frequencies of species and the estimation of population parameters”, Biometrika 40, pp. 237–264, Dec. 1953.

    MathSciNet  MATH  Google Scholar 

  3. A. Nadas: “On Turing’s formula for word probabilities”, IEEE Trans, on Acoustics, Speech and Signal Proc, Vol. ASSP-33, pp.1414–1416, Dec. 1985.

    Article  Google Scholar 

  4. S.M. Katz: “Estimation of probabilities from sparse data for the language model component of a speech recognizer”, IEEE Trans, on Acoustics, Speech and Signal Proc, Vol. SSP-35, pp. 400–401, March 1987.

    Article  Google Scholar 

  5. H. Ney, U. Essen: “On smoothing techniques for bigram-based natural language modelling”, Proc. ICASSP, Vol. 2, pp. 825–828, May 1991.

    Google Scholar 

  6. F. Jelinek, R.L. Mercer: “Interpolated estimation of Markov source parameters from sarse data”, pp. 381–397, in E.S. Gelsema, L.N. Kanal (eds.): Pattern Recognition in Practice, North-Holland Publ. Company, Amsterdam, 1980.

    Google Scholar 

  7. R. Kneser, H. Ney: “Improved clustering techniques for class-based statistical language modelling”, Proc. Eurospeech, Vol. 2, pp. 973–976 Sept. 1993.

    Google Scholar 

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© 1995 Springer-Verlag Berlin Heidelberg

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Kneser, R., Essen, U., Ney, H. (1995). On the Use of the Leaving-One-Out Method in Statistical Language Modelling. In: Ayuso, A.J.R., Soler, J.M.L. (eds) Speech Recognition and Coding. NATO ASI Series, vol 147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-57745-1_35

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  • DOI: https://doi.org/10.1007/978-3-642-57745-1_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-63344-7

  • Online ISBN: 978-3-642-57745-1

  • eBook Packages: Springer Book Archive

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