PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Probabilistic Finite State Automata - Part II
Enrique Vidal, Franck Thollard, Colin de la Higuera, Francisco Casacuberta and Rafael Carrasco
Pattern Analysis and Machine Intelligence Volume 27, Number 7, pp. 1026-1039, 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. We survey in this paper these objects, studying their definitions, how they relate to 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.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Natural Language Processing
Speech
Theory & Algorithms
ID Code:102
Deposited By:Colin de la Higuera
Deposited On:18 May 2004