2025 EMNLP EMNLP 2025

Discourse-Driven Code-Switching: Analyzing the Role of Content and Communicative Function in Spanish-English Bilingual Speech

Abstract

AbstractCode-switching (CSW) is commonly observed among bilingual speakers, and is motivated by various paralinguistic, syntactic, and morphological aspects of conversation. We build on prior work by asking: how do discourse-level aspects of dialogue – i.e. the content and function of speech – influence patterns of CSW? To answer this, we analyze the named entities and dialogue acts present in a Spanish-English spontaneous speech corpus, and build a predictive model of CSW based on our statistical findings. We show that discourse content and function interact with patterns of CSW to varying degrees, with a stronger influence from function overall. Our work is the first to take a discourse-sensitive approach to understanding the pragmatic and referential cues of bilingual speech and has potential applications in improving the prediction, recognition, and synthesis of code-switched speech that is grounded in authentic aspects of multilingual discourse.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary and Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio