SBIR/STTR Research Award

SBIR Phase I:Adaptive Dialog Systems As Second Language Learning Partners

Award identifier 52e20684c511903041672ef05e803ef5f708e4db1c19c00c25d1ce05446477d3Awarding agency National Science Foundation

Award amount

$256,000

Program and phase

SBIR · Phase I

Award year

2023

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Articulate.AI Inc
Proposal award date
2023-03-15
Contract end date
2023-11-30
UEI
R9THA4BEZVF6
Solicitation number
NSF 21-562
Topic code
AI

Research abstract

The broader impact of this Small Business Innovation Research (SBIR) Phase I project centers on offering a lower-cost, more accessible alternative to help people everywhere learn to speak a new language. By using state-of-the-art conversational artificial intelligence (AI), the project offers students individualized, curriculum-based learning that is affordable and accessible 24 hours a day, with no limits on the amount of time they can practice. Additionally, the AI system will be able to analyze learners’ speech to offer suggestions on ways to improve their grammar and conversational fluency, in much the same way a trained tutor would assist a student. The project brings conversational AI to the language learning market, enabling a more effective, entertaining, and low-cost product to transform the current language learning paradigm._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase I project is an innovative integration effort to combine state-of-the-art AI technologies for education applications. The project will contribute new user-adaptive algorithms and datasets for dialog policy training on language learning tasks. The project will contribute to the company’s open-source, multimodal, dialog system framework to enable the dialog community to reduce the entry barrier for multimodal dialog system research. The project will also provide the community with an annotated conversational dataset for grammatical error correction along with a trained grammar correction model and grammar error type detector. The developed educational dialog systems for second language communication learning can also serve as a general framework for education experts to test different learning theories. This project will also explore hypotheses of whether adaptive conversation experience and different feedback structures will impact learner confidence and learning gain._x000D_ _x000D_ 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.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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