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Probabilistic Finite State Automata - Part I
Enrique Vidal, Franck Thollard, Colin de la Higuera, Francisco Casacuberta and Rafael Carrasco
Pattern Analysis and Machine Intelligence
Volume 27,
Number 7,
,
2005.
Abstract Probabilistic finite state automata are used today in a variety of
areas in pattern recognition, or in fields to which pattern
recognition is linked: computational linguistics, machine learning,
time series analysis, circuit testing, computational biology, speech
recognition and machine translation are some of them. In part I of
this paper, we survey these objects and study their definitions
and properties. In part II, we will study the relation of
probabilistic finite state automata with other well known devices
that generate strings like hidden Markov models and n-grams, and
provide theorems, algorithms and properties that represent a current
state of the art of these objects. [Edit]
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