Jorge Valdes Kroff
$18,244
Jennifer Hu
Massachusetts Institute of Technology
Massachusetts
Social Behavioral and Economic Sciences (SBE)
DDRI Linguistics
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Humans interpret language in remarkably flexible ways. In particular, our interpretations involve not only what a speaker actually says, but also what the speaker could have said but didn't. For example, if someone says "some students passed the exam," listeners probably take this to mean that not all students passed, because the speaker could have used the more informative alternative "all students passed the exam" if that had been the case. Reasoning about these linguistic alternatives appears to play a key role in language comprehension, but it remains unclear how exactly the alternatives themselves are determined. When a speaker says something, what makes one sentence a better or worse alternative than another? How do alternatives depend on prior experience with different grammatical structures? And how might children learn the ability to reason about alternatives? This research project investigates these questions by combining linguistic theory, behavioral experiments, probabilistic modeling, and machine learning to test competing theories of alternatives. In doing so, this work has the potential to advance our understanding of language in the human mind, as well as artificial models that use language in human-like ways. The project also establishes opportunities for undergraduate researchers, and produce new code and datasets that will be publicly released to the broader scientific community.<br/><br/>In contrast to existing theories which suggest that alternatives are generated through operations on syntactic structures, this research evaluates the idea that alternatives capture experience-based accessibility relationships between the lexicon, grammar, and context. A planned series of behavioral experiments assess how the accessibility of alternatives affects the interpretation of event causation in English periphrastic causative constructions. In addition, model simulations investigate how knowledge of alternatives may emerge over the course of language learning, simultaneously establishing a framework for testing theories of alternatives in more ecologically valid domains.<br/><br/>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.