2023
ACL
ACL 2023
Measuring Lexico-Semantic Alignment in Debates with Contextualized Word Representations
Abstract
AbstractDialog participants sometimes align their linguistic styles, e.g., they use the same words and syntactic constructions as their interlocutors. We propose to investigate the notion of lexico-semantic alignment: to what extent do speakers convey the same meaning when they use the same words? We design measures of lexico-semantic alignment relying on contextualized word representations. We show that they reflect interesting semantic differences between the two sides of a debate and that they can assist in the task of debate’s winner prediction.
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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing