wav2letter

Facebook AI Research Automatic Speech Recognition Toolkit

Github星跟蹤圖

wav2letter++

CircleCI

wav2letter++ is a fast, open source speech processing toolkit from the Speech team at Facebook AI Research built to facilitate research in end-to-end models for speech recognition. 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.

This repository also contains pre-trained models and implementations for various ASR results including:

The previous iteration of wav2letter (written in Lua) can be found in the wav2letter-lua branch.

Building wav2letter++ and full documentation

All details and documentation can be found on the wiki.

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.

Finally, we provide Python bindings for a subset of wav2letter++ (featurization, decoder, and ASG criterion) and a standalone inference framework for running online ASR.

Citation

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

@article{pratap2018w2l,
  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.

License

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

主要指標

概覽
名稱與所有者flashlight/wav2letter
主編程語言C++
編程語言CMake (語言數: 8)
平台
許可證Other
所有者活动
創建於2017-11-20 17:39:41
推送於2024-11-23 22:29:28
最后一次提交
發布數5
最新版本名稱v0.2 (發布於 )
第一版名稱v0.1 (發布於 )
用户参与
星數6.4k
關注者數243
派生數1k
提交數473
已啟用問題?
問題數925
打開的問題數98
拉請求數6
打開的拉請求數10
關閉的拉請求數79
项目设置
已啟用Wiki?
已存檔?
是復刻?
已鎖定?
是鏡像?
是私有?