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 Alluzen'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
Installation
Add it to your Cargo.toml
:
[dependencies]
rustfst = "*"
Add extern crate rustfst
to your crate root and you are good to go!
Example
extern crate rustfst;
use transducer;
use ;
use VectorFst;
use ;
use Arc;
Documentation
The documentation of the last released version is available here : https://docs.rs/rustfst
Status
Not all the algorithms are (yet) implemented. This is work in progress.
License
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT) or http://opensource.org/licenses/MIT)
at your option.
Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.