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

建立自然对话的神经语言语料库来研究第二语言语法

• 批准号: 2203723
• 负责人: David Abugaber
• 金额: $ 13.8万
• 依托单位: Abugaber, David
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2203723&HistoricalAwards=false
• 关键词: Building; neurolinguistic; corpus; naturalistic; conversation

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.

该奖项是NSF的社会，行为和经济科学（SBE）博士后研究奖学金（SPRF）计划和SBE的语言学计划的一部分。SPRF计划的目标是为学术界，工业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的奖励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。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在密歇根大学Jonathan Brennan博士的赞助下，该博士后奖学金支持早期职业科学家研究母语和第二（L2）英语的语法处理机制。鉴于世界的相互联系日益紧密，以及讲一种以上语言的个人所表现出的好处，改进第二语言的教学方式是一个日益重要的领域。其中一个关键部分涉及理解学习者理解语法结构时所涉及的大脑机制。然而，以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，这些任务和刺激与典型的语言用户在真实的世界中遇到的不同。为了解决这个问题，我们的项目利用无线便携式大脑扫描和计算机语音识别的进步，以调查语法处理机制，在自然主义的会话在母语和第二语言（L2）的英语。脑电图（EEG）将记录在无脚本会话期间的母语和L2扬声器对和同步的转录。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。具体来说，我们测试了涉及抽象语法结构嵌套的分层模型（例如，使得类似于“在房子里”的短语涉及将“房子”作为内部子单元处理）与基于单词共同出现的频率的顺序模型（例如，“in”后面经常跟着“the”，“the”后面经常跟着“house”，等等）。目的1询问是否以前的研究结果的层次处理在本族语者听有声读物也适用于社会互动。目标2询问本族语者和第二语言使用者在加工的层次性和顺序性上是否存在差异。目的3转向社会语境机制，探讨语法加工的神经信号是否受到脑-脑同步性的影响。本研究揭示了二语输入的统计数据如何影响语法学习，从而为语言教学实践提供了参考。它还通过使用负担得起的便携式大脑扫描设备的“众包”实验设计来扩大神经科学的参与。最后，通过建立一个开放获取的自然无脚本对话语料库，音频，神经信号和转录可供未来的研究人员解决其他语言相关的研究问题。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。