Integrative mechanisms in human-human and human-robot communication across the adult lifespan.

口语的产生和理解速度惊人。例如，流利语音中的单词通常以每秒2或3个的速度生成，许多核心语言差异（例如区分单个语音声音的声学特性）取决于数十毫秒级别的时间差异。人类的思维如何科普口语的快速和动态特性？我们的研究计划的广泛目标是了解语言处理的速度和效率是如何从人类无意识地将联合收割机视觉和听觉信号与心理存储的知识相结合的特定方式中产生的。在我们过去的研究中，有一个主题探讨了实时理解如何利用听者对接下来要说的内容和形式的内隐期望。另一个主题探讨了听众在多大程度上迅速利用听觉信号中的细粒度声学细节。此外，通过比较年轻人和老年人（65岁以上），我们一直在努力了解沟通能力在成年人一生中的变化。 展望未来，我们目前研究的一个目标是了解语言处理的速度和效率是如何从语音信号本身之外的信息中产生的。交际的要求因语境而异，这可能会导致听者注意和利用潜在有用信息来源的方式发生有意识或无意识的变化。第二个目标是深入了解语言处理能力随着年龄的增长而变化的方式。 鉴于基本机制的复杂性，这一目标需要采取明确的方案办法，从许多不同角度收集证据。最后，考虑到技术的最新进展，一个越来越重要的话题是人类与配备有口语接口的人工智能体的交互。到目前为止，人们对人类如何适应或调整他们的口语和听力策略知之甚少。为了解决这个问题，我们已经开始使用人机通信来系统地识别哪些过程是在人们进行交流互动时自动发生的，哪些过程是在更有意识的控制下发生的。这项工作是用一个可编程的社交机器人进行的，该机器人的交流行为（例如，语音速率、语调、重音、停顿、眼睛注视模式）可以以细粒度的精度来控制。在所有这些研究中，我们采用敏感和适应性强的眼动追踪技术来揭示在毫秒级的真实的时间内遇到语言时理解过程的特征。 这项研究的结果将为我们与其他人或人工智能体交流时支持核心语言处理能力的认知架构提供重要见解。

Spoken language is produced and understood at a striking pace. For example, words in fluent speech are often generated at a rate of 2 or 3 per second, and many core linguistic distinctions (such as the acoustic properties that differentiate individual speech sounds) hinge on timing differences at the level of tens of milliseconds. How does the human mind cope with the rapid and dynamic nature of spoken language? The broad goals of our research program are to understand how the speed and efficiency of language processing result from the particular ways that humans unconsciously combine visual and auditory signals with mentally-stored knowledge. One theme in our past research explored how real-time comprehension draws on a listener's implicit expectations about the form and content of what will be said next. Another theme explored the extent to which listeners rapidly draw on fine-grained acoustic details in the auditory signal. Further, by making comparisons between younger and older (65+) adults, we have been working to understand how communicative abilities change over the course of the adult lifespan.  Going forward, one objective of our current research is to understand how the speed and efficiency of language processing arises from the information beyond the speech signal itself. Communicative requirements vary from context to context, and this may entail conscious or unconscious changes in the way that listeners attend to and draw on potentially helpful information sources. A second objective is to develop insights into the way that language processing abilities change as we age.  Given the complexity of the underlying mechanisms, this goal requires a clear programmatic approach involving converging evidence from many different angles. Finally, given recent advances in technology, one increasingly important topic involves humans' interactions with artificial agents equipped with spoken language interfaces. To date, comparatively little is known about how humans adapt or adjust their speaking and listening strategies in these scenarios. To address this issue, we have begun to use human-robot communication to systematically identify which processes occur automatically as people engage in communicative interaction, and which are under more conscious control. This work is conducted with a programmable social robot whose communicative behaviours (e.g., speech rate, intonation, accent, pauses, eye gaze patterns) can be controlled with fine-grained precision. In all of these studies, we employ sensitive and adaptable eye-tracking techniques to reveal the character of comprehension processes as language is encountered in real time at the millisecond level.  The outcomes of this research will provide important insights into the cognitive architecture that supports core language processing abilities as we communicate with other humans or with artificial agents.