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

Abugaber, David, Chicago IL

Investigators

Abstract

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.