Comparing Styles across Languages: A Cross-Cultural Exploration of Politeness
October 11, 2023 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
"No code URL or promise found in abstract"
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Authors
Shreya Havaldar, Matthew Pressimone, Eric Wong, Lyle Ungar
arXiv ID
2310.07135
Category
cs.CL: Computation & Language
Citations
2
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
5 months ago
Abstract
Understanding how styles differ across languages is advantageous for training both humans and computers to generate culturally appropriate text. We introduce an explanation framework to extract stylistic differences from multilingual LMs and compare styles across languages. Our framework (1) generates comprehensive style lexica in any language and (2) consolidates feature importances from LMs into comparable lexical categories. We apply this framework to compare politeness, creating the first holistic multilingual politeness dataset and exploring how politeness varies across four languages. Our approach enables an effective evaluation of how distinct linguistic categories contribute to stylistic variations and provides interpretable insights into how people communicate differently around the world.
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