2229873
Cooperative Agreement
Overview
Grant Description
AI Institute for Transforming Education for Children with Speech and Language Processing Challenges
It is estimated that more than 3.4 million children need speech and language related services in the US school system, yet there are less than sixty-one thousand speech-language pathologists (SLPs) to serve them. The COVID-19 pandemic has further exacerbated this gap, making it almost impossible for SLPs to provide individualized services for children.
The AI Institute for Transforming Education for Children with Speech and Language Processing Challenges aims to close this gap by developing advanced AI technologies to scale SLPs' availability and services such that no child in need of speech and language services is left behind. Towards this end, the institute proposes to develop two novel AI solutions:
(1) The AI Screener to enable universal early screening for all children, and
(2) The AI Orchestrator to work with SLPs to provide individualized interventions for children with their formal Individualized Educational Plan (IEP).
In developing these solutions, the institute will advance foundational AI technologies, enhance understanding of children's speech and language development, serve as a nexus point for special education stakeholders, and represent a fundamental paradigm shift in how SLPs serve children in need of ability-based speech and language services.
The AI Screener will be initially deployed in early childhood classrooms and will analyze video and audio streams of children's classroom interactions, derive conventional speech and language measures used by SLPs, and assess novel and hard to obtain automaticity measures.
The AI Orchestrator is a superset of the AI Screener with its main application in the public school classrooms. It will help SLPs to administer a wide range of evidence-based interventions and assess their effects on meeting children's individual IEP learning targets. At the core of the Orchestrator is a robust multi-agent reinforcement learning framework that can evaluate the potential benefits of different intervention practices and recommend those most appropriate for each child.
Both solutions will push significant advances in self-supervised learning to address sparse and noisy data issues, multimodality perception, learning material rewriting and enrichment, and edge AI for real-time processing. The institute will develop human-centered AI design methodologies to embody the solutions in a form appropriate for children's learning. Education research and the learning sciences will inform the initial prototyping and validation, and will derive valuable insights from the field deployed solutions.
The National Center for Special Education Research at the Institute of Education Sciences of the US Department of Education is partnering with NSF to provide funding for the institute. 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.
It is estimated that more than 3.4 million children need speech and language related services in the US school system, yet there are less than sixty-one thousand speech-language pathologists (SLPs) to serve them. The COVID-19 pandemic has further exacerbated this gap, making it almost impossible for SLPs to provide individualized services for children.
The AI Institute for Transforming Education for Children with Speech and Language Processing Challenges aims to close this gap by developing advanced AI technologies to scale SLPs' availability and services such that no child in need of speech and language services is left behind. Towards this end, the institute proposes to develop two novel AI solutions:
(1) The AI Screener to enable universal early screening for all children, and
(2) The AI Orchestrator to work with SLPs to provide individualized interventions for children with their formal Individualized Educational Plan (IEP).
In developing these solutions, the institute will advance foundational AI technologies, enhance understanding of children's speech and language development, serve as a nexus point for special education stakeholders, and represent a fundamental paradigm shift in how SLPs serve children in need of ability-based speech and language services.
The AI Screener will be initially deployed in early childhood classrooms and will analyze video and audio streams of children's classroom interactions, derive conventional speech and language measures used by SLPs, and assess novel and hard to obtain automaticity measures.
The AI Orchestrator is a superset of the AI Screener with its main application in the public school classrooms. It will help SLPs to administer a wide range of evidence-based interventions and assess their effects on meeting children's individual IEP learning targets. At the core of the Orchestrator is a robust multi-agent reinforcement learning framework that can evaluate the potential benefits of different intervention practices and recommend those most appropriate for each child.
Both solutions will push significant advances in self-supervised learning to address sparse and noisy data issues, multimodality perception, learning material rewriting and enrichment, and edge AI for real-time processing. The institute will develop human-centered AI design methodologies to embody the solutions in a form appropriate for children's learning. Education research and the learning sciences will inform the initial prototyping and validation, and will derive valuable insights from the field deployed solutions.
The National Center for Special Education Research at the Institute of Education Sciences of the US Department of Education is partnering with NSF to provide funding for the institute. 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.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NATIONAL ARTIFICIAL INTELLIGENCE (AI) RESEARCH INSTITUTES", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22502
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Buffalo,
New York
14228-2567
United States
Geographic Scope
Single Zip Code
Related Opportunity
The Research Foundation For The State University Of New York was awarded
AI Institute for Speech & Language Challenges in Education
Cooperative Agreement 2229873
worth $10,000,000
from the Division of Research on Learning in Formal and Informal Settings in January 2023 with work to be completed primarily in Buffalo New York United States.
The grant
has a duration of 5 years and
was awarded through assistance program 47.076 Education and Human Resources.
The Cooperative Agreement was awarded through grant opportunity National Artificial Intelligence (AI) Research Institutes.
Status
(Ongoing)
Last Modified 4/4/25
Period of Performance
1/15/23
Start Date
12/31/27
End Date
Funding Split
$10.0M
Federal Obligation
$0.0
Non-Federal Obligation
$10.0M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for 2229873
Transaction History
Modifications to 2229873
Additional Detail
Award ID FAIN
2229873
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
491109 DIV OF RESEARCH ON LEARNING IN
Funding Office
491109 DIV OF RESEARCH ON LEARNING IN
Awardee UEI
LMCJKRFW5R81
Awardee CAGE
3GQT6
Performance District
NY-26
Senators
Kirsten Gillibrand
Charles Schumer
Charles Schumer
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| STEM Education, National Science Foundation (049-0106) | General science and basic research | Grants, subsidies, and contributions (41.0) | $10,000,000 | 100% |
Modified: 4/4/25