ASAG

Automatic Short Answer Grading

Python Environment

Python version: 3.6.10

If you use Anaconda you can follow these steps:

conda create -n asag_pyenv python=3.6.10 

conda activate asag_pyenv 

If you already have a python 3.6 environment, you can ignore this step. Then install the requirements:

pip install -r requirements.txt 

python -m spacy download en

Download pre-trained word vectors

Download the Wikipedia 2014 + Gigaword 5 (6B tokens, 400K vocab, uncased, 50d, 100d, 200d, & 300d vectors, 822 MB download): glove.6B.zip

Unzip it and put it under ./model folder

experiment running

You can run the test example data by:

python train.py

Data augmentation

For data augmentation you may need another python environment

conda create -n aug_pyenv python=3.6

conda activate aug_pyenv 

Then install the requirements:

pip install sentencepiece==0.1.92

pip install googletrans==3.1.0a0

pip install EasyNMT==1.1.0

pip install xml4h

Then run the example:

python back_trans_aug.py

For the real time running, you need to change the parameters:

python back_trans_aug.py --src_path source_file_path --tar_path target_file_path --aug_src en --aug_tar fr