Welcome to DeepSpeech’s documentation!¶
DeepSpeech is an open source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu’s Deep Speech research paper. Project DeepSpeech uses Google’s TensorFlow to make the implementation easier.
To install and use DeepSpeech all you have to do is:
# Create and activate a virtualenv virtualenv -p python3 $HOME/tmp/deepspeech-venv/ source $HOME/tmp/deepspeech-venv/bin/activate # Install DeepSpeech pip3 install deepspeech # Download pre-trained English model files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.pbmm curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.scorer # Download example audio files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/audio-0.9.1.tar.gz tar xvf audio-0.9.1.tar.gz # Transcribe an audio file deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio audio/2830-3980-0043.wav
A pre-trained English model is available for use and can be downloaded following the instructions in the usage docs. For the latest release, including pre-trained models and checkpoints, see the GitHub releases page.
Quicker inference can be performed using a supported NVIDIA GPU on Linux. See the release notes to find which GPUs are supported. To run
deepspeech on a GPU, install the GPU specific package:
# Create and activate a virtualenv virtualenv -p python3 $HOME/tmp/deepspeech-gpu-venv/ source $HOME/tmp/deepspeech-gpu-venv/bin/activate # Install DeepSpeech CUDA enabled package pip3 install deepspeech-gpu # Transcribe an audio file. deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio audio/2830-3980-0043.wav
Please ensure you have the required CUDA dependencies.
See the output of
deepspeech -h for more information on the use of
deepspeech. (If you experience problems running
deepspeech, please check required runtime dependencies).
- Using a Pre-trained Model
- Training Your Own Model
- Prerequisites for training a model
- Getting the training code
- Creating a virtual environment
- Activating the environment
- Installing DeepSpeech Training Code and its dependencies
- Basic Dockerfile for training
- Common Voice training data
- Training a model
- Training with automatic mixed precision
- Exporting a model for inference
- Exporting a model for TFLite
- Making a mmap-able model for inference
- Fine-Tuning (same alphabet)
- Transfer-Learning (new alphabet)
- UTF-8 mode
- Supported platforms for inference
- Building DeepSpeech Binaries
There are several ways to contact us or to get help:
Discourse Forums - The Deep Speech category on Discourse is the first place to look. Search for keywords related to your question or problem to see if someone else has run into it already. If you can’t find anything relevant there, search on our issue tracker to see if there is an existing issue about your problem.
Create a new issue - Finally, if you have a bug report or a feature request that isn’t already covered by an existing issue, please open an issue in our repo and fill the appropriate information on your hardware and software setup.
- Error codes
- C API
- .NET Framework
- C API Usage example
- .NET API Usage example
- Java API Usage example
- Python API Usage example
- User contributed examples