In this paper, we propose an AI based approach to Trailer Generation in the form of short videos for online educational courses. Trailers give an overview of the course to the learners and help them make an informed choice about the courses they want to learn. It also helps to generate curiosity and interest among the learners and encourages them to pursue a course. While it is possible to manually generate the trailers, it requires extensive human efforts and skills over a broad spectrum of design, span selection, video editing, domain knowledge, etc., thus making it time-consuming and expensive, especially in an academic setting. The framework we propose in this work is a template based method for video trailer generation, where most of the textual content of the trailer is auto-generated and the trailer video is automatically generated, by leveraging Machine Learning and Natural Language Processing techniques. The proposed trailer is in the form of a timeline consisting of various fragments created by selecting, para-phrasing or generating content using various proposed techniques. The fragments are further enhanced by adding voice-over text, subtitles, animations, etc., to create a holistic experience. Finally, we perform user evaluation with 63 human evaluators for evaluating the trailers generated by our system and the results obtained were encouraging.
翻译:在本文中,我们提议以在线教育课程的短视频形式对拖车制作采用基于AI的方法。拖车向学员提供课程概况,帮助他们对其想学习的课程作出知情选择。还有助于激发学员的好奇心和兴趣,鼓励他们继续学习课程。虽然可以人工生成拖车,但需要广泛的设计、横跨选择、视频编辑、域知识等广泛的人的努力和技能,从而使得它耗费时间和费用,特别是在学术环境中。我们在此工作中提出的框架是视频拖车制作的模板方法,其中拖车的大部分文字内容是自动生成的,拖车视频是自动生成的,通过利用机器学习和自然语言处理技术自动生成的。拟议拖车的形式是由各种碎片组成的时间表,这些碎片由选择、副划线或利用各种拟议技术生成的内容组成。这些碎片通过添加超音频文本、字幕、动画等来进一步增强。最后,我们用63个人类评价员系统对所生成的拖车结果进行了用户评估,我们鼓励通过这些系统对产生的拖车进行评估。