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 and extract curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.5.1/deepspeech-0.5.1-models.tar.gz tar xvf deepspeech-0.5.1-models.tar.gz # Download example audio files curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.5.1/audio-0.5.1.tar.gz tar xvf audio-0.5.1.tar.gz # Transcribe an audio file deepspeech --model deepspeech-0.5.1-models/output_graph.pbmm --lm deepspeech-0.5.1-models/lm.binary --trie deepspeech-0.5.1-models/trie --audio audio/2830-3980-0043.wav
A pre-trained English model is available for use and can be downloaded using the instructions below. Currently, only 16-bit, 16 kHz, mono-channel WAVE audio files are supported in the Python client. A package with some example audio files is available for download in our release notes.
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-0.5.1-models/output_graph.pbmm --lm deepspeech-0.5.1-models/lm.binary --trie deepspeech-0.5.1-models/trie --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).
Table of Contents
- Using a Pre-trained Model
- Trying out DeepSpeech with examples
- Training your own Model
- Prerequisites for training a model
- Getting the training code
- Installing Python dependencies
- Common Voice training data
- Training a model
- Exporting a model for inference
- Exporting a model for TFLite
- Making a mmap-able model for inference
- Continuing training from a release model
- Training with Augmentation
- Contribution guidelines
- Contact/Getting Help