CNN-based and grammar-rules based model for native language identification based on speech transcripts.
These instructions will get you a copy of the project up and running on your machine for development purposes.
Create an environment with the required Python packages using your favorite package manager.
conda create --name <env> --file requirements.txt
To train a CNN model, run
python code/train.py
To do so with GPU support,
python code/train.py --cuda 0
see train.py help for more information.
Refer to the Evaluate.ipynb notebook for information on model evaluation.
This work is derived from data provided by the Educational Testing Services, copyright 2017 ETS (www.ets.org). The opinions set forth in this work are those of the authors and not ETS.
To the extent possible under law, the author(s) have dedicated all copyright and related and neighboring rights to this software to the public domain worldwide. This software is distributed without any warranty.
You should have received a copy of the CC0 Public Domain Dedication along with this software. If not, see http://creativecommons.org/publicdomain/zero/1.0/