Strategies of Code-switching in Human-Machine Dialogs

Dean Geckt, Melinda Fricke, Shuly Wintner
8/10/2025
cs.CLcs.AI

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Abstract

Most people are multilingual, and most multilinguals code-switch, yet the characteristics of code-switched language are not fully understood. We developed a chatbot capable of completing a Map Task with human participants using code-switched Spanish and English. In two experiments, we prompted the bot to code-switch according to different strategies, examining (1) the feasibility of such experiments for investigating bilingual language use, and (2) whether participants would be sensitive to variations in discourse and grammatical patterns. Participants generally enjoyed code-switching with our bot as long as it produced predictable code-switching behavior; when code-switching was random or ungrammatical (as when producing unattested incongruent mixed-language noun phrases, such as `la fork'), participants enjoyed the task less and were less successful at completing it. These results underscore the potential downsides of deploying insufficiently developed multilingual language technology, while also illustrating the promise of such technology for conducting research on bilingual language use.

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@article{geckt2025strategies,
  title  = {Strategies of Code-switching in Human-Machine Dialogs},
  author = {Dean Geckt and Melinda Fricke and Shuly Wintner},
  year   = {2025},
  eprint = {2508.07325},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.07325v1}
}

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