This repository creates a basis upon wich one can try out continual learning strategies on the Google Speech Command Dataset.
The Google Speech Command Dataset is composed of 35 classes of 1 second sound utturences. This dataset regroups words useful for robotics commands, and other words such as numbers and names.
This implementation is based on Avalanche a python library based on pytorch adapted to continual learning. This enables us to try out different continual learning strategies and models easily.
More information on this library can be found in their documentation and API.
Everything is logged with the python module sacred to a MongoDB database of your choosing.
To access this database and review/compare your experiments you can use a tool like omniboard.
To run your experiment:
- Run the
setup.shscript to create the necessary folders for the environment. - Move into the code directory using
cd src - Set the name of your experience and your desired parameters in the
cfg()function inmain.py - Run the experiment using
python3 main.py
The /web directory contains two Flask apps useful for creating a dataset and testing models on a website. For more info please refer to the /web/README.md file.