wav2letter++
Important Note:
wav2letter has been moved and consolidated into Flashlight in the ASR application.
Future wav2letter development will occur in Flashlight.
To build the old, pre-consolidation version of wav2letter, checkout the wav2letter v0.2 release, which depends on the old Flashlight v0.2 release. The wav2letter-lua project can be found on the wav2letter-lua branch, accordingly.
For more information on wav2letter++, see or cite this arXiv paper.
Recipes
This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducability. Papers contained here include:
- Pratap et al. (2020): Scaling Online Speech Recognition Using ConvNets
- Synnaeve et al. (2020): End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
- Kahn et al. (2020): Self-Training for End-to-End Speech Recognition
- Likhomanenko et al. (2019): Who Needs Words? Lexicon-free Speech Recognition
- Hannun et al. (2019): Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions
Data preparation for training and evaluation can be found in data directory.
Building the Recipes
First, install Flashlight (using the 0.3 branch is required) with the ASR application.
mkdir build && cd build
cmake .. && make -j8If Flashlight or ArrayFire are installed in nonstandard paths via a custom CMAKE_INSTALL_PREFIX, they can be found by passing
-Dflashlight_DIR=[PREFIX]/usr/share/flashlight/cmake/ -DArrayFire_DIR=[PREFIX]/usr/share/ArrayFire/cmakewhen running cmake.
Join the wav2letter community
- Facebook page: https://www.facebook.com/groups/717232008481207/
- Google group: https://groups.google.com/forum/#!forum/wav2letter-users
- Contact: [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected]
License
wav2letter++ is MIT-licensed, as found in the LICENSE file.