Crate rustfst

Rustfst

Rust implementation of Weighted Finite States Transducers.

Rustfst 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 label equal. 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 key applications in speech recognition and synthesis, machine translation, optical character recognition, pattern matching, string processing, machine learning, information extraction and retrieval among others. Often a weighted transducer is used to represent a probabilistic model (e.g., an n-gram model, pronunciation model). FSTs can be optimized by determinization and minimization, models can be applied to hypothesis sets (also represented as automata) or cascaded by finite-state composition, and the best results can be selected by shortest-path algorithms.

References

Implementation heavily inspired from Mehryar Mohri's, Cyril Allauzen's and Michael Riley's work :

• Weighted automata algorithms
• The design principles of a weighted finite-state transducer library
• OpenFst: A general and efficient weighted finite-state transducer library
• Weighted finite-state transducers in speech recognition

Example

// Creates a empty wFST
let mut fst = VectorFst::new();

// Add some states
let s0 = fst.add_state();
let s1 = fst.add_state();
let s2 = fst.add_state();

// Set s0 as the start state
fst.set_start(s0).unwrap();

// Add an arc from s0 to s1
fst.add_arc(s0, Arc::new(3, 5, IntegerWeight::new(10), s1))
    .unwrap();

// Add an arc from s0 to s2
fst.add_arc(s0, Arc::new(5, 7, IntegerWeight::new(18), s2))
    .unwrap();

// Set s1 and s2 as final states
fst.set_final(s1, IntegerWeight::new(31)).unwrap();
fst.set_final(s2, IntegerWeight::new(45)).unwrap();

// Iter over all the paths in the wFST
for p in fst.paths_iter() {
    println!("{:?}", p);
}

Status

Not all algorithms are (yet) implemented, this is still work in progress.

Modules

algorithms	Provides algorithms that are generic to all wFST.
fst_impls	Implementation of the wFST traits with different data structures.
fst_traits	Provides traits that must be implemented to be able to use generic algorithms.
semirings	Provides a trait that shall be implemented for all weights stored inside a wFST.
utils	A few utilities to manipulate wFSTs.

Macros

fst	Creates a linear Fst containing the arguments.
fst_path	Creates a Path containing the arguments.
symt	Creates a SymbolTable containing the arguments.

Structs

Arc	Structure representing a transition from a state to another state in a FST.
DrawingConfig	Struct to configure how the FST should be drawn.
FstPath	Structure representing a path in a FST (list of input labels, list of output labels and total weight).
SymbolTable	A symbol table stores a bidirectional mapping between arc labels and "symbols" (strings).

Constants

EPS_LABEL	Epsilon label representing the epsilon transition (empty transition) = 0.
EPS_SYMBOL	Epsilon symbol representing the epsilon transition (empty transition) = <eps>.

Type Definitions

Label	Type used for the input label and output label of an arc in a wFST -> usize
StateId	Type used to identify a state in a wFST -> usize
Symbol	Symbol to map in the Symbol Table -> String