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1. de la Higuera, C.; Oncina, J.
   "Computing the Most Probable String with a Probabilistic Finite State Machine"
   Proceedings of the 11th International Conference on Finite State Methods and Natural Language Processing, pp. 1-8 (2013)
   : bibtex : pdf
   Abstract:

   The problem of finding the consensus / most probable string for a distribution generated by a probabilistic finite automaton or a hidden Markov model arises in a number of natural language processing tasks: it has to be solved in several transducer related tasks like opti- mal decoding in speech, or finding the most probable translation of an input sentence. We provide an algorithm which solves these prob- lems in time polynomial in the inverse of the probability of the most probable string, which in practise makes the computation tractable in many cases. We also show that this exact com- putation compares favourably with the tradi- tional Viterbi computation.

@inproceedings {
 author = "de la Higuera, C.; Oncina, J.",
 title  = "Computing the Most Probable String with a Probabilistic Finite State Machine",
 booktitle = "Proceedings of the 11th International Conference on Finite State Methods and Natural Language Processing",
 editor = "Mark-Jan Nederhof ",
 month = "July",
 pages = "1-8",
 publisher = "Association for Computational Linguistics ",
 year = "2013"
}