CAREER: Developing an integrated model of speech entrainment

夹带现象是会话双方在不同方面表现得更加相似的现象，是分析会话的一个重要特征。它在人与人之间的交流中非常常见，与高质量的对话有关。由于越来越多的重要对话发生在人类和虚拟对话代理之间，这样的代理能够缠住使用它的人，以增加他们之间的融洽关系，这将是有用的。然而，关于夹带仍然有很多未知之处，比如什么导致了夹带，为什么人们会以不同的方式夹带。这个职业项目的目标是了解更多关于夹带的知识，以改善人机沟通，更好地理解人与人之间的沟通。这个项目将开发一个综合的夹带模式，即对话伙伴现象？通过分析多个已知或假想的影响夹带的因素的相互作用和效果大小，使言语变得更加相似，这些因素包括说话人的特征，如性别、个性和自闭症；交互特征，如喜好和支配；以及话语特征，如对话行为或情感。将收集一个自发对话的语料库来支持这一分析。使用的方法将包括统计和因果分析，以及非线性机器学习方法的新应用，以模拟每个说话人对他们的对话者的影响。这个项目的贡献将是更深入和更具体地理解夹带可以告诉我们关于对话的什么，以及应该如何在虚拟对话代理中建模。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Entrainment, the phenomenon of conversational partners' behaving more like each other in various ways, is an important feature for analyzing conversations. It is very common in human-human communication and is associated with high-quality conversations. Because more and more important conversations are happening between humans and virtual conversational agents, it would be useful for such an agent to be able to entrain on the person using it, to increase the rapport between them. However, there is still a lot that is still not known about entrainment, such as what causes it and why people entrain in different ways. The goal of this CAREER project is to learn more about entrainment in order to improve human-computer communication and to better understand human-human communication. This project will develop an integrated model of entrainment, the phenomenon of conversational partners? speech becoming more similar to each other, by analyzing the interactions and effect sizes of multiple factors known or hypothesized to affect entrainment, including speaker features such as gender, personality, and autism; interactional features such as liking and dominance; and utterance features such as dialog act or emotion. A corpus of spontaneous conversations will be collected to support the analysis. The methods used will include statistical and causal analysis, as well as a novel application of nonlinear machine learning methods to model the influence of each speaker on their interlocutor. The contribution of this project will be a deeper and more specific understanding of what entrainment can tell us about a conversation and how it should be modeled in a virtual conversational agent.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.