Counting 3,567 Big Data & Machine Learning Frameworks, Toolsets, and Examples...
Suggestion? Feedback? Tweet @stkim1

Last Commit
Feb. 22, 2019
Nov. 20, 2017


wav2letter++ is a fast open source speech processing toolkit from the Speech Team at Facebook AI Research. It is written entirely in C++ and uses the ArrayFire tensor library and the flashlight machine learning library for maximum efficiency. Our approach is detailed in this arXiv paper.

The goal of this software is to facilitate research in end-to-end models for speech recognition.

The previous version of wav2letter (written in Lua) can be found in the "wav2letter-lua" branch under the repository.

Building wav2letter++

See Building Instructions for details.

Full documentation

To get started with wav2letter++, checkout the tutorials section.

We also provide complete recipes for WSJ, Timit and Librispeech and they can be found in recipes folder.


If you use the code in your paper, then please cite it as:

  author          = {Vineel Pratap, Awni Hannun, Qiantong Xu, Jeff Cai, Jacob Kahn, Gabriel Synnaeve, Vitaliy Liptchinsky, Ronan Collobert},
  title           = {wav2letter++: The Fastest Open-source Speech Recognition System},
  journal         = {CoRR},
  volume          = {abs/1812.07625},
  year            = {2018},
  url             = {},

Join the wav2letter community

See the CONTRIBUTING file for how to help out.


wav2letter++ is BSD-licensed, as found in the LICENSE file.

Latest Releases
Initial Release
 Dec. 21 2018