Probabilistic finite-state machines - Part I.

Enrique Vidal (1) , Franck Thollard (2) , Colin de La Higuera (2) , Francisco Casacuberta (1) , Rafael C. Carrasco (3)

1 UPV - Universitat Politècnica de València
2 LHC - Laboratoire Hubert Curien
3 UPA - Universitad Politecnica de Alicante

Probabilistic finite-state machines 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 generative 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 as hidden Markov models and -grams, and provide theorems, algorithms and properties that represent a current state of the art of these objects.

Domains: Artificial Intelligence [cs.AI]

Enrique Vidal, Franck Thollard, Colin de La Higuera, Francisco Casacuberta, Rafael C. Carrasco. Probabilistic finite-state machines - Part I.. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27 (7), pp.1013-1025. ⟨ujm-00326243⟩