PyTorch reimplementation of Google's TensorFlow convolutional neural networks for keyword spotting, which accompanies the recent release of their Speech Commands Dataset. For more details, please consult our writeup:
- Raphael Tang, Jimmy Lin. Honk: A PyTorch Reimplementation of Convolutional Neural Networks for Keyword Spotting. arXiv:1710.06554, October 2017.
This is useful for building on-device speech recognition capabilities for interactive intelligent agents. can be used to identify simple commands (e.g., "stop" and "go") and be adapted to detect custom "command triggers" (e.g., "Hey Siri!").
Use the instructions below to run the demo application (shown in the above video) yourself!
To deploy the demo, run the following commands:
- If you do not have PyTorch, please see the website.
- Install Python dependencies:
pip install -r requirements.txt - Install GLUT (OpenGL Utility Toolkit) through your package manager (e.g.
apt-get install freeglut3-dev) - Start the PyTorch server:
python . - Run the demo:
python utils/speech_demo.py
If you need to adjust options, like turning off CUDA, please edit config.json.
Additional notes for Mac OS X:
- GLUT is already installed on Mac OS X, so that step isn't needed.
- If you have issues installing pyaudio, this may be the issue.