The Sensitivity of the Modified Viterbi Algorithm to the Source Statistics

Rajjan Shinghal, Godfried T. Toussaint

Research output: Contribution to journalArticlepeer-review


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
Issue number2
StatePublished - Mar 1980


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

ASJC Scopus subject areas

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


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