Code-switching (CSW) in speech is motivated by conversational factors across levels of linguistic analysis. While we know much about why speakers code-switch, there remains great scope for exploring how CSW occurs in speech, particularly within the discourse-level linguistic context. We build on prior work by asking: how are patterns of CSW influenced by different conversational contexts spanning Academic, Cultural, Personal, and Professional discourse topics? To answer this, we annotate a Mandarin-English spontaneous speech corpus, and analyze its discourse topics alongside various aspects of CSW production. We show that discourse topics interact significantly with utterance-level CSW, resulting in distinctive patterns of CSW presence, richness, language direction, and syntax that are uniquely associated with different contexts. Our work is the first to take such a context-sensitive approach to studying CSW, contributing to a broader understanding of the discourse topics that motivate speakers to code-switch in diverse ways.

It is well-known that speakers who entrain to one another have more successful conversations than those who do not. Previous research has shown that interlocutors entrain on linguistic features in both written and spoken monolingual domains. More recent work on code-switched communication has also shown preliminary evidence of entrainment on certain aspects of code-switching (CSW). However, such studies of entrainment in code-switched domains have been extremely few and restricted to human-machine textual interactions. Our work studies code-switched spontaneous speech between humans, finding that (1) patterns of written and spoken entrainment in monolingual settings largely generalize to code-switched settings, and (2) some patterns of entrainment on code-switching in dialogue agent-generated text generalize to spontaneous code-switched speech. Our findings give rise to important implications for the potentially “universal” nature of entrainment as a communication phenomenon, and potential applications in inclusive and interactive speech technology.