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

SBIR 第一阶段：自适应对话系统作为第二语言学习伙伴

• 批准号: 2213202
• 负责人: Zhou YU
• 金额: $ 25.6万
• 依托单位: Articulate.AI Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-15 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213202&HistoricalAwards=false
• 关键词: SBIR; Phase; Adaptive; Dialog; Systems

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.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.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.

我项目的更广泛的影响是通过使用最先进的对话（AI）提供更低成本，更容易获得的交替的人。罐头练习。市场，实现更有效，娱乐性和低成本的产品来改变您当前的语言paradigmm.this小企业创新研究（SBIR）I阶段项目是一种创新的集成，可以结合用于教育应用的ART AI技术。该项目将为对话的新用户自适应算法和数据集进行学习任务的政策培训。系统研究也将使用训练有素的语法校正模型和语法范围的语法数据集。以及不同的反馈结构信心和学习增长。这反映了NSF的统计任务，并值得支持基金会的知识分子优点影响审查。