• DocumentCode
    1060254
  • Title

    Kneser–Ney Smoothing With a Correcting Transformation for Small Data Sets

  • Author

    Taraba, Peter

  • Author_Institution
    Smart Desktop, Seattle
  • Volume
    15
  • Issue
    6
  • fYear
    2007
  • Firstpage
    1912
  • Lastpage
    1921
  • Abstract
    We present a technique which improves the Kneser-Ney smoothing algorithm on small data sets for bigrams, and we develop a numerical algorithm which computes the parameters for the heuristic formula with a correction. We give motivation for the formula with correction on a simple example. Using the same example, we show the possible difficulties one may run into with the numerical algorithm. Applying the algorithm to test data we show how the new formula improves the results on cross-entropy.
  • Keywords
    entropy; maximum likelihood estimation; optimisation; probability; smoothing methods; speech recognition; Kneser-Ney smoothing algorithm; bigrams; correcting transformation; cross-entropy; heuristic formula; maximum-likelihood estimation; numerical algorithm; probability; small data sets; speech processing; speech recognition; Character recognition; Entropy; Handwriting recognition; Maximum likelihood detection; Maximum likelihood estimation; Optical character recognition software; Smoothing methods; Speech recognition; Testing; Speech processing; speech recognition;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TASL.2007.900090
  • Filename
    4276766