Project Grant 0644097

This National Science Foundation (NSF) Project Grant, awarded under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), provides $457,997 to Indiana University to build a 1.4-million-word syntactically parsed electronic corpus spanning 900 years of a single language. The corpus will allow researchers to investigate grammatical change and variation over time, as well as enable comparisons to similar developments in related languages. The project involves manual annotation of...

This two-year, $262,952 project grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of a hybrid-architecture symbolic parser and neural lexicon system (HASPNEL) at the University of Puerto Rico. HASPNEL uses a feature-unification parser and structure generator encoded with symbolic AI to judge whether an utterance is grammatical and detect ambiguity at...

The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $484,509 Project Grant to The Ohio State University to develop a computational model for extracting world knowledge from pre-trained language models and applying it to improve the accuracy of grammar induction from text. The project, titled "COMPCOG: RI: SMALL: HUMAN-LIKE SEMANTIC GRAMMAR INDUCTION THROUGH KNOWLEDGE DISTILLATION FROM PRE-TRAINED LANGUAGE MODELS", aims to create a semantic...

This $449,275 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to advance the scientific understanding of human language processing and change. The project, led by the University of California, Davis (UC Davis), combines expertise from linguistics, psychology, and computational approaches to investigate how language users integrate general language constraints and verb-specific preferences...

This two-year, $205,570 project grant from the National Science Foundation's Division of Computer and Network Systems will support the development of a Hybrid-Architecture Symbolic Parser with Neural Lexicon (HASPNEL) system. Funded under the Computer and Information Science and Engineering program, this collaborative research between the University of Arizona and the State of Arizona aims to advance natural language processing technologies through a novel hybrid computational model. The HASPNEL...

This National Science Foundation (NSF) award under the Computer and Information Science and Engineering program (CFDA 47.070) provides $299,977 to Trustees of Indiana University to develop five new syntactically-annotated corpora of endangered languages. The project aims to build high-quality datasets and computational tools for analyzing the grammars of these languages, validating new techniques that can work with small datasets. The key products include: (1) five freely-available treebanks...

This $386,226 National Science Foundation project grant supports research and educational activities at the University of Massachusetts related to representing and learning stress patterns in human languages. Specifically, the grant funds work applying machine learning techniques from computer science to test competing linguistic theories about how word stress systems are represented mentally and acquired. It also examines using neural networks, an understudied representation approach in...

This National Science Foundation project grant award of $116,990 supports research into deconstructing wordlikeness judgments through interconnected experimental and computational studies. Funded under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), the award will provide research training and mentoring opportunities for graduate students in modern experimental and computational methods related to phonotactic knowledge and language sciences. Specifically, the City University...

This three-year National Science Foundation project grant of $439,222 will fund research into the typology of subordinate clauses across languages at the University of Rochester from August 2022 to July 2025. The project has two main components. The first is a large-scale data collection effort using novel elicitation methods to study subordinate clause inferences in an under-resourced language. The second develops a computational model to identify semantic predicate classes across unrelated...

This two-year, $138,000 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program will support research examining syntactic regulation and adaptation in bidialectal and heritage bilingual speakers. The goal is to better understand the nature and consequences of proficient, multidialectal language experience. Under the sponsorship of Dr. Julie Washington at the University of California, Irvine, the postdoctoral fellow will conduct a neurolinguistic...