标题： 人机对话中的代码转换策略 显示英文标题

标题： Strategies of Code-switching in Human-Machine Dialogs

摘要： 大多数人是双语的，大多数双语者会进行语言转换，但语言转换的特点尚未完全被理解。 我们开发了一个聊天机器人，能够使用西班牙语和英语的语言转换与人类参与者一起完成地图任务。 在两个实验中，我们根据不同的策略提示机器人进行语言转换，考察（1）此类实验对于研究双语语言使用的可行性，以及 （2）参与者是否会对话语和语法模式的变化敏感。 只要机器人产生可预测的语言转换行为，参与者通常都喜欢与机器人进行语言转换；当语言转换是随机的或不正确的（例如生成未出现的不一致混合语言名词短语，如“la fork”），参与者对任务的喜爱程度降低，并且完成任务的成功率也较低。 这些结果强调了部署不够完善的多语言技术可能带来的负面影响，同时也展示了这种技术在研究双语语言使用方面的潜力。 显示英文摘要

摘要： 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.