This 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, natural language processing
and information retrieval. Typically a weighted transducer is used to represent
either hypothesis sets (e.g., *speech lattices*) or probabilistic models (e.g., *language models*
or *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.

Topic revision: r7 - 2006-11-21 - CyrilAllauzen

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