# MFST: A Python OpenFST Wrapper With Support for Custom Semirings and Jupyter Notebooks

arXiv: https://arxiv.org/abs/2012.03437 · HTML: https://mlsanity.com/paper/2012.03437/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Dec 2020.

## Built on by (most cited first, 1 of 1)

- [Lexically Aware Semi-Supervised Learning for OCR Post-Correction](https://mlsanity.com/paper/2111.02622/) (2021)

## Abstract (arXiv)

This paper introduces mFST, a new Python library for working with Finite-State Machines based on OpenFST. mFST is a thin wrapper for OpenFST and exposes all of OpenFST's methods for manipulating FSTs. Additionally, mFST is the only Python wrapper for OpenFST that exposes OpenFST's ability to define a custom semirings. This makes mFST ideal for developing models that involve learning the weights on a FST or creating neuralized FSTs. mFST has been designed to be easy to get started with and has been previously used in homework assignments for a NLP class as well in projects for integrating FSTs and neural networks. In this paper, we exhibit mFST API and how to use mFST to build a simple neuralized FST with PyTorch.