Technology Category
Natural Language Processing: Code Generation / Program Synthesis from Natural LanguageHumans and AI: User Experience and UsabilityIntelligent Robots: Human-Robot Interaction
Strategies of Code-switching in Human-Machine Dialogs
🤖 AI Summary
This study addresses the lack of empirical research on code-switching mechanisms (Spanish/English) in human–machine bilingual dialogue. We developed a task-oriented chatbot and conducted controlled map-task experiments to systematically evaluate distinct code-switching strategies—namely, rule-driven, grammatically compliant, and predictable versus random or ungrammatical switching. Through human-participant interaction studies, we provide the first empirical evidence that grammatical well-formedness and pattern predictability of code-switching significantly improve task completion efficiency and user experience; users consistently prefer structured, linguistically constrained language mixing. Our findings establish critical empirical foundations for designing multilingual AI dialogue systems, underscoring that controllability and linguistic plausibility of code-switching are essential for effective human–AI collaboration.
Technology Category
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Understanding code-switching behavior in multilingual human-machine dialogs
Evaluating chatbot strategies for code-switching in Spanish-English interactions
Assessing participant sensitivity to discourse and grammatical pattern variations
Innovation
Methods, ideas, or system contributions that make the work stand out.
Chatbot performs Map Task with code-switching
Tests code-switching strategies in bilingual dialogs
Analyzes user sensitivity to grammatical patterns
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