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

该奖项是作为NSF社会、行为和经济科学(SBE)博士后研究奖学金(SPRF)计划和SBE语言学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。在密歇根大学乔纳森·布伦南博士的赞助下，这一博士后奖学金奖项支持一名研究以英语为母语和第二语言(L2)的语法处理机制的早期职业科学家。鉴于世界日益相互联系，以及会说一种以上语言对个人的好处日益明显，改进第二语言的教学方式是一个日益重要的领域。这其中的一个关键部分涉及理解学习者理解语法结构时所涉及的大脑机制。然而，之前关于语言处理的大脑研究通常涉及孤立的实验室环境中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脑扫描和计算机化语音识别的进步来研究母语和第二语言(L2)英语自然对话背后的语法处理机制。脑电(EEG)将在母语和L2说话者对之间的无脚本对话期间被记录下来，并与转录同步。观察到的数据将与基于不同可能的语法机制的计算机模型的预测进行比较。具体地说，我们测试涉及抽象语法结构的嵌套的分层模型(例如，使得像“in the house”这样的短语涉及将“the house”处理为内部子单元)与基于单词共同出现的频率的顺序模型(例如，“in”通常后跟“the”，“the”通常后跟“house”，等等)。目标1询问以前关于本族语有声读物听力的分层加工的发现是否也适用于社会互动。目标2询问母语者和二语使用者在加工的层次性和顺序性上是否存在差异。目的3从社会语境的机制出发，探讨脑与脑的同步性是否影响语法加工的神经表征。本研究通过揭示二语输入的统计数据对语法学习的影响，为语言教学实践提供参考。它还通过使用价格合理的便携式脑扫描设备的“众包”实验设计，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访问语料库，音频、神经信号和转录可供未来的研究人员用于解决其他与语言相关的研究问题。这一奖项反映了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 (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.