NAACL 2024short3 citations
Extracting Lexical Features from Dialects via Interpretable Dialect Classifiers
Roy Xie, Orevaoghene Ahia, Yulia Tsvetkov, Antonios Anastasopoulos
Abstract
Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis. This is largely due to the complexity and nuance involved in studying various dialects. We present a novel approach to extract distinguishing lexical features of dialects by utilizing interpretable dialect classifiers, even in the absence of human experts. We explore both post-hoc and intrinsic approaches to interpretability, conduct experiments on Mandarin, Italian, and Low Saxon, and experimentally demonstrate that our method successfully identifies key language-specific lexical features that contribute to dialectal variations.
BibTeX
@inproceedings{xie-etal-2024-extracting,
title = "Extracting Lexical Features from Dialects via Interpretable Dialect Classifiers",
author = "Xie, Roy and
Ahia, Orevaoghene and
Tsvetkov, Yulia and
Anastasopoulos, Antonios",
editor = "Duh, Kevin and
Gomez, Helena and
Bethard, Steven",
booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.naacl-short.5/",
doi = "10.18653/v1/2024.naacl-short.5",
pages = "54--69"
}