rustfst-python 0.10.0

Library for constructing, combining, optimizing, and searching weighted finite-state transducers (FSTs). Re-implementation of OpenFst in Rust.

Rustfst

Rust

Python

This repo contains a Rust implementation of Weighted Finite States Transducers. Along with a Python binding.

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

use anyhow::Result;
use rustfst::prelude::*;
use rustfst::algorithms::determinize::{DeterminizeType, determinize};
use rustfst::algorithms::rm_epsilon::rm_epsilon;

fn main() -> Result<()> {
    // Creates a empty wFST
    let mut fst = VectorFst::<TropicalWeight>::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)?;

    // Add a transition from s0 to s1
    fst.add_tr(s0, Tr::new(3, 5, 10.0, s1))?;

    // Add a transition from s0 to s2
    fst.add_tr(s0, Tr::new(5, 7, 18.0, s2))?;

    // Set s1 and s2 as final states
    fst.set_final(s1, 31.0)?;
    fst.set_final(s2, 45.0)?;

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

    // A lot of operations are available to modify/optimize the FST.
    // Here are a few examples :

    // - Remove useless states.
    connect(&mut fst)?;

    // - Optimize the FST by merging states with the same behaviour.
    minimize(&mut fst)?;

    // - Copy all the input labels in the output.
    project(&mut fst, ProjectType::ProjectInput);

    // - Remove epsilon transitions.
    rm_epsilon(&mut fst)?;

    // - Compute an equivalent FST but deterministic.
    fst = determinize(&fst)?;

    Ok(())
}

Benchmark with OpenFST

I did a benchmark some time ago on almost every linear fst algorithm and compared the results with OpenFst. You can find the results here :

• Benchmark at the C++ level
• Benchmark at the CLI level

Spoiler alert: Rustfst is faster on all those algorithms 😅

Documentation

The documentation of the last released version is available here : https://docs.rs/rustfst

Release process

1. Use the script update_version.sh to update the version of every package.
2. Push
3. Push a new tag with the prefix rustfst-v

Example :

./update_version.sh 0.9.1-alpha.6
git commit -am "Release 0.9.1-alpha.6"
git push
git tag -a rustfst-v0.9.1-alpha.6 -m "Release rustfst 0.9.1-alpha.6"  
git push --tags

Optionally, if this is a major release, create a GitHub release in the UI.

Projects contained in this repository

This repository contains two main projects:

• rustfst is the Rust re-implementation.
  • Crate available on crates.io here
  • Documentation available on docs.rs here
• rustfst-python is the python binding of rustfst.
  • Package available on Pypi here
  • Documentation available on Github Pages here

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.