Device-DS as a window into mechanisms of speech production: An investigation of adults and children

该奖项是作为NSF社会、行为和经济学博士后研究奖学金(SPRF)计划的一部分提供的。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在加州大学戴维斯分校的周瑜博士、乔治亚·泽洛博士和凯瑟琳·格拉夫·埃斯特斯博士的赞助下，这项博士后奖学金支持一位早期职业科学家探索个人在与声控人工智能(语音-AI)设备交谈时如何调整自己的语音，如亚马逊的Alexa或苹果的Siri，这些设备正成为日常生活中无处不在的功能。这个项目调查了成年人和儿童参与语音人工智能的方式；目前，人们对这些智能设备交谈时如何调整语音知之甚少。研究人与设备的交互对于考察人与技术之间不断变化的关系非常重要；随着数字设备变得越来越普遍，了解它们对我们的交流和社交行为的影响至关重要。这个项目探索了成人和儿童在与成人人类对话者交谈时，如何调整他们的语音。这项工作提供了一种方法来检验不同的理论预测，即语音语域调整在多大程度上是由功能动机(如可理解性)和社会因素(如性别)驱动的。例如，这项研究探索了在纠正人类对话者的理解错误时，同样的功能动机是否也适用于设备定向言语(DS)，例如操纵错误的语音性质，以仔细控制交际中与可理解性相关的压力水平。同时，本项目探讨了社会因素如何影响言语适应策略，如对话者类型、说话人年龄或设备性别。该项目还包括在直接通过数字设备平台编程和运行实验方面的重要方法创新。总体而言，该项目旨在填补我们在与语音人工智能设备交谈时在声学-语音调整方面的知识空白，并最终能够揭示不同说话者语音产生的潜在机制(例如，基于年龄、性别、设备经验)，为基础科学研究做出贡献。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。

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Zhou Yu, Dr. Georgia Zellou, and Dr. Katharine Graf Estes at the University of California, Davis, this postdoctoral fellowship award supports an early career scientist exploring how individuals adjust their speech when talking to voice-activated artificially intelligent (voice-AI) devices, such as Amazon's Alexa or Apple's Siri, which are becoming ubiquitous features of everyday life. This project investigates the ways in which adults and children engage with voice-AI; currently little is known about how people adjust their speech when talking to these smart devices. Studying human-device interaction is important to examine the changing relationship between humans and technology; as digital devices become more prevalent, it is critical to understand their impact on our communicative and social behavior. This project explores the ways in which adults and children adapt their speech when talking to voice-activated digital assistants (e.g., Amazon's Alexa), compared to adult human interlocutors. This line of work provides a way to test differing theoretical predictions as to the extent that speech-register adjustments are driven by functional motives (e.g., intelligibility) and social factors (e.g., gender). For instance, this research explores whether the same functional motivations that apply when correcting comprehension errors to human interlocutors apply in device-directed speech (DS), such as in manipulating the phonological nature of errors, to carefully control the level of intelligibility-related pressures in communication. At the same time, this project explores how social factors may impact speech adaptation strategies, such as by interlocutor type, speaker age, or device gender. This project additionally involves important methodological innovations in programming and running experiments directly through a digital device platform. Overall, this project aims to fill a gap in our knowledge in the acoustic-phonetic adjustments humans make when talking to voice-AI devices, and can ultimately reveal the underlying mechanisms in speech production by different speakers (e.g., based on age, gender, device experience), contributing to basic science research.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.