Title :
Probabilistic finite-state machines - part II
Author :
Vidal, Enrique ; Thollard, Frank ; de la Higuera, C. ; Casacuberta, Francisco ; Carrasco, Rafael C.
Author_Institution :
Departamento de Sistemas Informaticos y Computacion, Univ. Politecnica de Valencia, Spain
fDate :
7/1/2005 12:00:00 AM
Abstract :
Probabilistic finite-state machines are used today in a variety of areas in pattern recognition or in fields to which pattern recognition is linked. In part I of this paper, we surveyed these objects and studied their properties. In this part, we study the relations between probabilistic finite-state automata and 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.
Keywords :
finite state machines; hidden Markov models; pattern recognition; probabilistic automata; hidden Markov models; n-grams; pattern recognition; probabilistic finite-state automata; probabilistic finite-state machines; Computer Society; Hidden Markov models; Learning automata; Machine learning; Machine learning algorithms; Natural languages; Pattern recognition; Probability distribution; Speech recognition; Stochastic processes; Index Terms- Automata; classes defined by grammars or automata; language acquisition; language models; language parsing and understanding; machine learning; machine translation; speech recognition and synthesis; structural pattern recognition; syntactic pattern recognition.; Algorithms; Artificial Intelligence; Cluster Analysis; Computer Simulation; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Signal Processing, Computer-Assisted;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2005.148
