The Sensitivity of the Modified Viterbi Algorithm to the Source Statistics

Rajjan Shinghal, Godfried Toussaint

    Research output: Contribution to journalArticle

    Abstract

    The modified Viterbi algorithm is a powerful, and increasingly used, tool for using contextual information in text recognition in its various forms. As yet, no known studies have been published concerning its robustness with respect to source statistics. This paper describes experiments performed to determine the sensitivity of the algorithm to variations in source statistics. The results of the experiments show that a character-recognition machine incorporating the modified Viterbi algorithm, using N-gram statistics estimated from source A does not deteriorate in performance when operating on a passage from source B even if A and B differ significantly in TV-gram distributions or entropy.

    Original languageEnglish (US)
    Pages (from-to)181-185
    Number of pages5
    JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
    VolumePAMI-2
    Issue number2
    DOIs
    StatePublished - Jan 1 1980

    Fingerprint

    Viterbi Algorithm
    Viterbi algorithm
    Statistics
    Character recognition
    N-gram
    Character Recognition
    Entropy
    Experiments
    Experiment
    Robustness

    Keywords

    • Character recognition
    • contextural information
    • entropy
    • Markov process
    • natural language statistics
    • robustness tests
    • text processing
    • Viterbi algorithm

    ASJC Scopus subject areas

    • Software
    • Computer Vision and Pattern Recognition
    • Computational Theory and Mathematics
    • Artificial Intelligence
    • Applied Mathematics

    Cite this

    The Sensitivity of the Modified Viterbi Algorithm to the Source Statistics. / Shinghal, Rajjan; Toussaint, Godfried.

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-2, No. 2, 01.01.1980, p. 181-185.

    Research output: Contribution to journalArticle

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