Building a neurolinguistic corpus of naturalistic conversation to investigate second language grammar

该奖项是国家科学基金会社会、行为和经济科学（SBE）博士后研究奖学金（SPRF）项目和SBE语言学项目的一部分。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事业准备有前途的早期职业博士级科学家。SPRF奖励包括在知名科学家的赞助下进行为期两年的培训，并鼓励博士后进行独立研究。美国国家科学基金会寻求促进科学界各阶层的科学家，包括那些未被充分代表的群体的科学家，参与其研究项目和活动；博士后阶段被认为是实现这一目标的一个重要的专业发展阶段。每个博士后必须解决各自学科领域的重要科学问题。在密歇根大学的乔纳森·布伦南博士的赞助下，该博士后奖学金支持研究母语和第二语言（L2）英语语法处理机制的早期职业科学家。考虑到世界日益紧密的联系，以及讲多种语言对个人的好处，改进第二语言的教学方式是一个日益重要的领域。其中一个关键部分是理解学习者理解语法结构时所涉及的大脑机制。然而，先前关于语言处理的大脑研究通常涉及在孤立的实验室环境中进行的人工实验任务和刺激，这与典型的语言使用者在现实世界中遇到的情况不同。为了解决这一障碍，我们的项目利用无线便携式大脑扫描和计算机语音识别技术的进步来研究母语和第二语言（L2）英语自然对话的语法处理机制。脑电图（EEG）将在母语和第二语言说话者之间的无脚本对话中记录下来，并与转录同步。观察到的数据将与基于不同可能语法机制的计算机模型的预测进行比较。具体来说，我们测试了涉及抽象语法结构嵌套的层次模型（例如，像“在房子里”这样的短语涉及将“房子”作为一个内部子单元处理）与基于单词共出现频率的顺序模型（例如，“在”后面经常跟“the”，“the”后面经常跟“house”等）。目的1询问以前关于以母语为母语的人听有声读物时的层次加工的发现是否也适用于社会互动。目标2询问母语和第二语言使用者在加工的层次性和顺序性方面是否存在差异。目的3转向社会情境的机制，探讨语法加工的神经特征是否受到脑对脑同步的影响。这项工作通过揭示第二语言输入的统计数据如何影响语法学习，为语言教学实践提供了信息。它还通过使用“可众包”的实验设计和负担得起的便携式脑部扫描设备，扩大了对神经科学的参与。最后，通过建立自然无脚本对话的开放获取语料库，音频、神经信号和转录可用于未来的研究人员解决其他与语言相关的研究问题。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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 (SBE) Postdoctoral Research Fellowships (SPRF) program and SBE's Linguistics 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. Jonathan Brennan at the University of Michigan, this postdoctoral fellowship award supports an early career scientist studying grammar processing mechanisms in native and second (L2) English. Given the increasing interconnectedness of the world as well as the demonstrated benefits to individuals of speaking more than one language, improving the way that second languages are taught is an area of growing importance. A critical part of this involves understanding the brain mechanisms that are involved when learners comprehend grammatical structures. However, previous brain research on language processing has typically involved artificial experimental tasks and stimuli in isolated laboratory settings that are different from what a typical language user encounters in the real world. To address this obstacle, our project harnesses advances in wireless portable brain-scanning and computerized speech recognition to investigate the grammar processing mechanisms that underlie naturalistic conversation in native and second language (L2) English.Electroencephalograms (EEG) will be recorded during unscripted conversation between native and L2 speaker pairs and synchronized with transcriptions. The observed data will be compared against predictions from computer models based on different possible mechanisms of grammar. Specifically, we test hierarchical models involving nesting of abstract grammatical structures (e.g., such that a phrase like “in the house” involves processing “the house” as an internal subunit) versus sequential models based on how often words co-occur (e.g., “in” is often followed by “the,” “the” is often followed by “house,” etc.). Objective 1 asks whether previous findings of hierarchical processing in native speaker audiobook listening also hold for social interaction. Objective 2 asks whether native and L2 speakers differ in the hierarchical vs. sequential nature of their processing. Objective 3 turns to the mechanisms of social context to ask whether neural signatures of grammar processing are affected by brain-to-brain synchrony. This work informs language teaching praxis by revealing how the statistics of L2 input affect grammar learning. It also broadens participation in neuroscience by using a “crowdsource-able” experiment design with affordable portable brain-scanning devices. Finally, by building an open-access corpus of natural unscripted conversation, the audio, neural signals, and transcriptions are available to future researchers to address other language-related research questions.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.