The National Science Foundation (NSF) awarded a $208,058 Project Grant to Trustees of Boston University to conduct collaborative research on quantifying sign reduction in sign language using human pose estimation. The research project, funded through the NSF's Social, Behavioral, and Economic Sciences program (CFDA 47.075), investigates phonetic variation in signed languages by analyzing patterns of sign articulation. The researchers leverage computer vision techniques to extract anatomical...
This National Science Foundation project grant of $149,999 supports research on American Sign Language grammar through 2026. Funded under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), the collaborative project will analyze usage of specific ASL signs in online videos to contribute to understanding ASL structure. It will establish best practices for accessible research using internet data and increase participation of deaf linguists. Specifically, researchers will collect...
This project grant from the National Science Foundation's Division of Behavioral and Cognitive Sciences, under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), provides $149,999 to Gallaudet University to study American Sign Language usage. The university will collaborate with deaf researchers to analyze instances of "what" signs in a large sample of American Sign Language videos posted online. Through this analysis, the project aims to contribute to understanding...
The National Science Foundation (NSF) Division of Behavioral and Cognitive Sciences awarded a $444,630 Project Grant to the Regents of the University of Michigan to investigate how signers and gesturers communicate about everyday activities and events. The project, funded through the Social, Behavioral, and Economic Sciences program (CFDA 47.075), will examine communication in sign language by deaf signers, communication in gesture by hearing speakers, and communication in sign language by...
This $150,000 National Science Foundation project grant supports research on American Sign Language usage and grammar through analysis of online video data. Funded under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), the collaborative project between The University of New Mexico and deaf researchers aims to 1) contribute to understanding ASL grammar patterns, 2) establish best practices for analyzing internet video data, and 3) increase deaf participation in linguistic...
The National Science Foundation (NSF) awarded a $170,130 Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the Rochester Institute of Technology (RIT) to create a large sign language corpus with annotations focused on capturing understudied characteristics of visual prosody and its grammatical and emotional functions. The project aims to develop best practices for representing these characteristics in the corpus, provide open access teaching modules,...
This National Science Foundation (NSF) Project Grant award, under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program, provides $129,730 to Gallaudet University in Washington, D.C. to create a large corpus of annotated sign language dialogues that capture understudied characteristics of visual prosody and its grammatical and emotional functions. The project aims to develop a tested method for representing these linguistic features, establish best practices for continued use of...
This $170,000 Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports an early career postdoctoral research fellowship investigating the emergence of phonological structure in a family homesign system. Under the sponsorship of Dr. Diane Brentari at the University of Chicago, the research project aims to compare linguistic variation among deaf siblings who developed their own family homesign system, and to draw...
This National Science Foundation Project Grant of $628,966 will fund research from August 2022 to July 2025 to develop technologies for recognizing American Sign Language (ASL) from continuous signing videos. The award was made under the Computer and Information Science and Engineering program (CFDA 47.070), which supports research and education in computing and information sciences. The grantee, Rutgers University, and its partners will create a novel machine learning approach with three key...
This $165,014 National Science Foundation project grant will fund the development of linguistically-driven sign recognition technologies from continuous American Sign Language (ASL) signing videos. The Rochester Institute of Technology will receive funding under the Computer and Information Science and Engineering program (CFDA 47.070) to advance sign recognition techniques for isolated citations to segmented signs within sentences. The research will create an end-to-end machine learning...