Code for the paper: Symbolic inductive bias for visually grounded learning of spoken language. https://arxiv.org/abs/1812.09244, published at ACL 2019.
Clone repo and set up and activate a virtual environment with python3
cd symbolic-bias
virtualenv -p python3 .
Install Python code (in development mode if you will be modifying something).
python setup.py develop
Download trained models and unpack them:
wget http://grzegorz.chrupala.me/data/symbolic-bias/experiments.tgz
tar zxvf experiments.tgz
Download data and unpack them:
wget http://grzegorz.chrupala.me/data/symbolic-bias/data.tgz
tar zxvf data.tgz
Execute function main in file analysis/analyze.py.
cd analysis
python -c 'import analyze; analyze.main()'
The output should be similar to analysis/results.tex.
Inspect the definition of this function to see how to compute the results from each table in the paper.