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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛影响是提供更低成本，更容易获得的替代方案，以帮助各地的人们学习讲一种新语言。通过使用最先进的对话人工智能（AI），该项目为学生提供个性化的，基于课程的学习，每天24小时可负担且易于访问，而他们可以练习的时间无限。此外，AI系统将能够分析学习者的演讲，以提出有关提高语法和对话流利的方法的建议，就像训练有素的导师可以帮助学生一样。该项目将对话性AI带到了语言学习市场，从而实现了更有效，娱乐和低成本的产品，以改变当前的语言学习Paradigmm。该小型企业创新研究（SBIR）I阶段项目是一项创新的整合努力，以结合用于教育应用程序的最先进的AI AI技术。该项目将为对话培训语言学习任务的对话策略培训提供新的用户自适应算法和数据集。该项目将有助于公司的开源，多式模式，对话系统框架，以使对话框社区减少多模式对话系统研究的进入障碍。该项目还将为社区提供带注释的对话数据集，以进行语法误差校正以及训练有素的语法校正模型和语法误差类型检测器。用于第二语言交流学习的开发的教育对话系统还可以作为教育专家测试不同学习理论的一般框架。该项目还将探讨自适应对话经验和不同的反馈结构是否会影响学习者的信心和学习收益。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估评估的评估来支持的。