Facebook AI Research Automatic Speech Recognition Toolkit
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jacobkahn and facebook-github-bot Fix gpu select_compute_arch for nvcc flags to work with CMake 3.5.1
Fixes the CUDA criterion backend build for CMake 3.5.1:
- Removes features from `select_compute_arch.cmake` which were CMake 3.6+ for 3.5.1 compatibility
- Reverts to `cuda_include_directories`. `cub` and project base path header dirs are included in global nvcc scope, because `target_include_directories` isn't supported on CUDA library targets in CMake 3.5.1.

Reviewed By: andresy

Differential Revision: D13742260

fbshipit-source-id: 15ba2be0c2c087315a867ffe878ce90eff91bd25
Latest commit 304b62d Jan 18, 2019



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             = {https://arxiv.org/abs/1812.07625},

Join the wav2letter community

See the CONTRIBUTING file for how to help out.


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