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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).
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CyrilAllauzen - 25 May 2007
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MichaelRiley - 25 May 2007