Comparing Styles across Languages: A Cross-Cultural Exploration of Politeness

October 11, 2023 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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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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