AI Institute for Transforming Education for Children with Speech and Language Processing Challenges

据估计，在美国学校系统中，超过340万儿童需要语音和语言相关服务，但只有不到61000名语音语言病理学家（SLP）为他们提供服务。COVID-19大流行进一步加剧了这一差距，使SLP几乎不可能为儿童提供个性化服务。人工智能研究所旨在通过开发先进的人工智能技术来缩小这一差距，以扩大SLP的可用性和服务，使需要语音和语言服务的儿童不会落后。为此，研究所建议开发两种新型人工智能解决方案：（1）人工智能筛查器，为所有儿童提供普遍的早期筛查，以及（2）人工智能干预器，与SLP合作，为具有正式个性化教育计划（IEP）的儿童提供个性化干预。 在开发这些解决方案时，该研究所将推进基础人工智能技术，增强对儿童言语和语言发展的理解，作为特殊教育利益相关者的联系点，并代表了SLP如何为需要基于能力的语音和语言服务的儿童提供服务的根本范式转变。AI Screener最初将部署在幼儿教室中，并将分析儿童的课堂互动，获得传统的语音和语言的措施所使用的SLP，并评估新的和难以获得的自动性措施。 AI Screener是AI Screener的超集，主要应用于公立学校的教室。它将帮助辅助学习计划实施一系列以实证为基础的干预措施，并评估其对实现儿童个人IEP学习目标的影响。 该系统的核心是一个强大的多智能体强化学习框架，可以评估不同干预措施的潜在好处，并为每个孩子推荐最合适的干预措施。 这两种解决方案都将推动自监督学习的重大进展，以解决稀疏和噪声数据问题，多模态感知，学习材料重写和丰富，以及用于真实的时间处理的边缘AI。该研究所将开发以人为本的人工智能设计方法，以适合儿童学习的形式体现解决方案。教育研究和学习科学将为最初的原型设计和验证提供信息，并将从实地部署的解决方案中获得有价值的见解。美国教育部教育科学研究所的国家特殊教育研究中心与NSF合作，为该研究所提供资金。该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响评审标准。

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.