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OpenFst Library

OpenFst is a library for constructing, combining, optimizing, and searching weighted finite-state transducers (FSTs). Weighted finite-state transducers are automata where each transition has an input label, an output label, and a weight. The more familiar finite-state acceptor is represented as a transducer with each transition's input and output the same. Finite-state acceptors are used to represent sets of strings (specifically, regular or rational sets); finite-state transducers are used to represent binary relations between pairs of strings (specifically, rational transductions). The weights can be used to represent the cost of taking a particular transition.

FSTs have been applied to a variety of problems in speech and text processing, OCR, and information retrieval. Typically a weighted transducer is used to represent either hypothesis sets (e.g., word lattices) or probabilistic models (e.g., ngram models, pronunciation models). The FSTs can be optimized by determinization and minimization, models can be applied to hypothesis sets via finite-state composition, and the best results can be selected by shortest-path algorithms.

This library was developed at Google Research (M. Riley, J. Schalkwyk, W. Skut) and NYU's Courant Institute (C. Allauzen, M. Mohri).

-- CyrilAllauzen
-- MichaelRiley

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Topic revision: r18 - 2007-06-14 - MichaelRiley
 
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