STTR Phase I: Authoring Tools for Virtual Role-Play

STTR 第一阶段：虚拟角色扮演创作工具

• 批准号: 1549752
• 负责人: Brenda Lindsay
• 金额: $ 22.44万
• 依托单位: Alelo TLT LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1549752&HistoricalAwards=false
• 关键词: STTR; Phase; Authoring; Tools; Virtual

This SBIR Phase I project will develop a revolutionary new tool for creating engaging language-learning content. Educational publishers, teachers, and even students will be able to create artificially intelligent "virtual role-players" that converse in foreign languages, responding to either speech or text input. Large-scale on-line communities of educators will be able to create, customize, and share their own virtual role-play content, thus changing how people learn foreign languages. This will have a major impact on world language education and will help the US develop a more globally competent workforce. Many schools, especially in rural and underserved areas, have difficulty maintaining foreign language programs due to lack the resources to hire sufficient qualified teachers. This innovation will greatly increase the availability of high-quality interactive language learning resources that engage learners. These will be available online at little or no cost to schools. This could have a broad impact on world language enrollments as well as student retention in world language programs. In the longer term, virtual role-play can have a broad disruptive impact on training and workforce development. Employers are increasingly concerned about the skill gaps in the workforce, and communication and other 21st century skills are coming to the fore. This project will establish the technical and commercial feasibility of a new tool and platform that enables non-programmers to create sophisticated virtual role-play simulations for learning foreign languages and other communicative skills. Competing can construct linear role-play scenarios, but are not suitable for creating interactive role-play simulations in which learners can take the initiative and where there are multiple possible outcomes. To break down the problem and make authoring feasible for teachers and students, the project will focus first on a significant, commonly occurring component of such dialogs, namely context-specific natural-language question-answering. The tool will automatically train a statistical language understanding system to recognize target questions so the virtual role-player can respond to them. This data-driven approach ensures that as users create content the body of training data continues to grow, making it ever easier to create new content. The toolset will help manage the necessary training data. The approach has the potential to change world language education from a teacher-led, classroom-centric activity to a personalized, learner-centric activity. It can flip the language classroom in ways that watching videos online cannot, by helping learners develop their conversational skills outside of class.

SBIR 第一阶段项目将开发一种革命性的新工具，用于创建引人入胜的语言学习内容。教育出版商、教师甚至学生将能够创建人工智能“虚拟角色扮演者”，用外语进行对话，对语音或文本输入做出反应。大型在线教育工作者社区将能够创建、定制和共享他们自己的虚拟角色扮演内容，从而改变人们学习外语的方式。这将对世界语言教育产生重大影响，并将帮助美国培养更具全球竞争力的劳动力。许多学校，尤其是农村和服务欠缺地区的学校，由于缺乏资源聘请足够的合格教师，难以维持外语课程。这项创新将大大增加吸引学习者的高质量交互式语言学习资源的可用性。这些内容将在线提供，学校只需支付很少费用或免费。这可能会对世界语言的入学率以及世界语言课程的学生保留率产生广泛的影响。从长远来看，虚拟角色扮演可以对培训和劳动力发展产生广泛的颠覆性影响。雇主越来越关注劳动力的技能差距，而沟通和其他 21 世纪技能正在脱颖而出。该项目将建立新工具和平台的技术和商业可行性，使非程序员能够创建复杂的虚拟角色扮演模拟来学习外语和其他交流技能。竞争可以构建线性角色扮演场景，但不适合创建交互式角色扮演模拟，在这种模拟中，学习者可以采取主动，并且有多种可能的结果。为了解决这个问题并使创作对教师和学生来说变得可行，该项目将首先关注此类对话中一个重要且常见的组成部分，即特定于上下文的自然语言问答。该工具将自动训练统计语言理解系统来识别目标问题，以便虚拟角色扮演者能够回答这些问题。这种数据驱动的方法可确保随着用户创建内容，训练数据体不断增长，从而使创建新内容变得更加容易。该工具集将帮助管理必要的培训数据。该方法有可能将世界语言教育从教师主导、以课堂为中心的活动转变为个性化、以学习者为中心的活动。它可以帮助学习者在课外培养对话技能，从而以在线观看视频无法实现的方式翻转语言课堂。