espnet | EndtoEnd Speech Processing Toolkit | Speech library

by espnet Python Version: v.202204 License: Apache-2.0

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kandi X-RAY | espnet Summary

espnet is a Python library typically used in Artificial Intelligence, Speech, Deep Learning, Pytorch applications. espnet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install espnet' or download it from GitHub, PyPI.

Docs | Example | Example (ESPnet2) | Docker | Notebook | Tutorial (2019). ESPnet is an end-to-end speech processing toolkit covering end-to-end speech recognition, text-to-speech, speech translation, speech enhancement, speaker diarization, spoken language understanding, and so on. ESPnet uses pytorch as a deep learning engine and also follows Kaldi style data processing, feature extraction/format, and recipes to provide a complete setup for various speech processing experiments.

Support

Quality

Security

License

Reuse

kandi-support Support

espnet has a medium active ecosystem.
It has 4934 star(s) with 1562 fork(s). There are 178 watchers for this library.
There were 2 major release(s) in the last 6 months.
There are 257 open issues and 1487 have been closed. On average issues are closed in 369 days. There are 62 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of espnet is v.202204

espnet Support

Best in #Speech

Average in #Speech

espnet Support

Best in #Speech

Average in #Speech

quality kandi Quality

espnet has no bugs reported.

espnet Quality

Best in #Speech

Average in #Speech

espnet Quality

Best in #Speech

Average in #Speech

security Security

espnet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

espnet Security

Best in #Speech

Average in #Speech

espnet Security

Best in #Speech

Average in #Speech

license License

espnet is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.

espnet License

Best in #Speech

Average in #Speech

espnet License

Best in #Speech

Average in #Speech

build Reuse

espnet releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.

espnet Reuse

Best in #Speech

Average in #Speech

espnet Reuse

Best in #Speech

Average in #Speech

Top functions reviewed by kandi - BETA

kandi has reviewed espnet and discovered the below as its top functions. This is intended to give you an instant insight into espnet implemented functionality, and help decide if they suit your requirements.

Recognize beam .
Runs an ESPPnet model .
Train the train function .
r Bayesian Diagonal Diagonal Diagonalization .
Main worker function .
Arguments for the feed - forward transformer model .
Train one epoch .
Traverse audio files .
Forward inference .
Recompose encoder .

espnet Key Features

End-to-End Speech Processing Toolkit

espnet Examples and Code Snippets

Community Discussions

Vulnerabilities

No vulnerabilities reported

Install espnet

If you intend to do full experiments including DNN training, then see Installation.
If you intend to do full experiments including DNN training, then see Installation.
If you just need the Python module only: # We recommend you installing pytorch before installing espnet following https://pytorch.org/get-started/locally/ pip install espnet # To install latest # pip install git+https://github.com/espnet/espnet # To install additional packages # pip install "espnet[all]" If you'll use ESPnet1, please install chainer and cupy. pip install chainer==6.0.0 cupy==6.0.0 # [Option] You might need to install some packages depending on each task. We prepared various installation scripts at tools/installers.
(ESPnet2) Once installed, run wandb login and set --use_wandb true to enable tracking runs using W&B.

Support

Thank you for taking times for ESPnet! Any contributions to ESPnet are welcome and feel free to ask any questions or requests to issues. If it's the first contribution to ESPnet for you, please follow the contribution guide.