Code for the 2024 Linguistic Inquiry paper A Learning-Based Account of Phonological Tiers.
@article{belth2024tiers,
title={A Learning-Based Account of Phonological Tiers},
author={Belth, Caleb},
journal={Linguistic Inquiry},
year={2024},
publisher={MIT Press},
url = {https://doi.org/10.1162/ling\_a\_00530},
}
The results are in the results/
directory. If you wish to reproduce them, please see the script exp.py
in the experiments
directory. The script takes two arguments:
--exp-name / -e, type=str (one of Turkish-CHILDES|Turkish-Morpho|Finnish|Latin)
--model / -m type=str, (one of D2L|GR|trigram|TSLIA|GG|LSTM)
exp-name
specifies which dataset to produce the results for. model
specifies which model to run. The results are saved in the directory results/{exp_name}/{model}
.
D2L is implemented in the Python package algophon. I recommend that implementation for running the model on your own data—just pip install algophon
!