Automatic Processing of Spoken and Written Lecture Material

在过去的十年里，我们看到在线学术讲座材料的可获得性急剧增加。然而，值得注意的是，与许多其他交际活动相比，到目前为止，演讲处理几乎没有享受到人类语言技术的发展带来的好处。这项提议的目标是使人们能够快速、准确和方便地获取授课内容。我们将在语音识别、结构归纳和摘要领域开发新技术。我们的工作将有助于更好地理解书面语和口语之间的关系，这是语言学中一个长期存在的问题，但实证研究有限。我们的研究将通过在不同层面上对这种关系进行广泛的语料库研究来纠正这种情况，从词汇到语篇变化。我们建议开发的工具将在麻省理工学院开放课程倡议的框架内进行集成和测试，该倡议是一个大型的公开在线教材库，来自500门麻省理工学院的课程。此外，我们还将把我们的工具纳入解放学习倡议，该倡议致力于让残疾学生融入主流高等教育。

In the past decade, we have seen a dramatic increase in the availability ofon-line academic lecture material. It is conspicuous, however, that in contrastto many other communicative activities, lecture processing has until nowenjoyed little benefit from the development of human language technology. Thegoal of this proposal is to enable fast, accurate and easy access to lecturecontent. We will develop new technologies in the area of speech recognition,structure induction and summarization.Our work will contribute to a better understanding of the relationship betweenwritten and spoken language, a long standing issue in linguistics which hasseen limited empirical research. Our research will rectify this situation byan extensive corpus-based study of this relationship at different levels,ranging from vocabulary to discourse variations.The tools we propose to develop will be integrated and tested in the frameworkof the MIT Open CourseWare Initiative, a large publicly available on-linerepository of teaching material from 500 MIT courses. In addition, wewill also incorporate our tools in the Liberated Learning Initiative, whichworks on the integration of students with disabilities in mainstream highereducation.