Age of Exposure 2.0: Estimating word complexity using Iterative Models of Word Embeddings

This repository contains the training and inference code for the "Age of Exposure - Word Learning using Iterative Models of Word Embeddings" paper.

Not included:

• The "Touchstone Applied Science Associates, Inc." corpus
• The "Corpus of Contemporary American English" corpus
• The Childes Child-Directed Speech corpora (https://childes.talkbank.org/)

Included:

• train_models.py: trains incremental Word2Vec models
• compute_indices.py: computes word indices used for predicting AoE scores
• evaluate_aoa.py: evaluates models using a set of indices
• generate_aoe_v2_predictions.py: trains using AoA norms and runs inference on the entire corpus vocabulary
• run_experiment.sh: calls all scripts in order, given a quantiles file and an experiment name
• train_model_multilingual_aoe_v2.py: training code for Multilingual AoE 2.0

Environment set-up

Install Anaconda: https://www.anaconda.com/products/individual And load the environment from the yml file:

conda env create -f environment.yml

Then you can activate the environment:

conda activate age_of_exposure_v2

And download other necessary resources:

python -m spacy download en_core_web_lg

License

Apache 2.0. Please review the "LICENSE" file in the root of this directory.

Contact

Please contact us through the emails listed on the papers in the references section.

Resources

• resources/AoEv1.csv: the indices from the AoE 1.0
• resources/predicted_AoE2_vocab_sorted_linear_rf_tasa_coca_cds.csv: predicted AoA scores for the best performing model in AoE 2.0
• resources/multilingual_aoe_v2_[de|en|es|fr]: predicted AoA scores for the best performing model in Multilingual Age of Exposure 2.0

References

Dascalu, M., McNamara, D., Crossley, S., & Trausan-Matu, S. (2016, March). Age of exposure: a model of word learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 30, No. 1).

Botarleanu, R. M., Dascalu, M., Watanabe, M., McNamara, D. S., & Crossley, S. A. (2021, June). Multilingual Age of Exposure. In International Conference on Artificial Intelligence in Education (pp. 77-87). Springer, Cham.

Botarleanu, R.-M., Dascalu, M., Watanabe, M., Crossley, S. A., & McNamara, D. S. (submitted). Age of Exposure 2.0: Estimating Word Complexity using Iterative Models of Word Embeddings. Behavior Research Methods.

Acknowledgement

This research was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS – UEFISCDI, project number TE 70 PN-III-P1-1.1-TE-2019-2209, ATES – “Automated Text Evaluation and Simplification”, the Institute of Education Sciences (R305A180144 and R305A180261), and the Office of Naval Research (N00014-17-1-2300; N00014-20-1-2623). The opinions expressed are those of the authors and do not represent views of the IES or ONR. We would also like to thank Prof. Peter Foltz for providing the Word Maturity indices that were used as a baseline in the previous papers.