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Proceedings of the 6th ACM Conference on Conversational User Interfaces. ACM Conference on Conversational User Interfaces (6th : 2024 : Luxembourg, Luxembourg)最新文献

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Say What? Real-time Linguistic Guidance Supports Novices in Writing Utterances for Conversational Agent Training. 你说什么?实时语言指导支持新手写作话语会话代理训练。
Rachel Ostrand, Kristina Brimijoin, David Piorkowski, Jessica He, Erica Albert, Stephanie Houde

Writing utterances to train conversational agents can be a challenging and time-consuming task, and usually requires substantial expertise, meaning that novices face a steep learning curve. We investigated whether novices could be guided to produce utterances that adhere to best practices via an intervention of real-time linguistic feedback. We conducted a user study in which participants were tasked with writing training utterances for a particular topic (intent) for a conversational agent. Participants received one of two types of linguistic guidance in real-time to shape their utterance-writing: (1) feedback on the lexical and syntactic properties and the variety of each utterance, or (2) sample utterances written by other users, to select or inspire the writing of new utterances. All participants also completed a control condition, in which they wrote utterances for a different intent without receiving any guidance. We investigated whether linguistic properties of the utterances differed as a function of whether the participant had received guidance, and if so, which type. Results showed that participants wrote longer and better quality utterances, with greater lexical and syntactic diversity, in both guidance conditions compared to when they received no guidance. These results demonstrate that giving novices explicit linguistic guidance can improve the quality of the training utterances they write, suggesting that this could be an effective way of getting new utterance writers started with much less training than most current practices require.

编写话语来训练会话代理可能是一项具有挑战性和耗时的任务,通常需要大量的专业知识,这意味着新手面临着陡峭的学习曲线。我们调查了新手是否可以通过实时语言反馈的干预来指导产生符合最佳实践的话语。我们进行了一项用户研究,其中参与者的任务是为会话代理编写特定主题(意图)的训练话语。参与者收到两种语言指导中的一种,以实时塑造他们的话语写作:(1)对词汇和句法特性的反馈以及每个话语的多样性,或(2)其他用户写的样本话语,以选择或启发新话语的写作。所有参与者还完成了一个控制条件,在这个条件下,他们在没有任何指导的情况下写下不同意图的话语。我们调查了话语的语言特性是否因参与者是否接受了指导而有所不同,如果接受了指导,则是哪种类型。结果显示,与没有接受指导的情况相比,在两种指导条件下,参与者都能写出更长、质量更好的话语,词汇和句法的多样性也更大。这些结果表明,给予新手明确的语言指导可以提高他们所写的训练话语的质量,这表明这可能是一种有效的方法,可以让新的话语作者开始用比目前大多数实践所需的训练少得多的训练。
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Proceedings of the 6th ACM Conference on Conversational User Interfaces. ACM Conference on Conversational User Interfaces (6th : 2024 : Luxembourg, Luxembourg)
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