AI based approach to trailer generation for online educational courses

Prakhar Mishra, Chaitali Diwan, Srinath Srinivasa, G. Srinivasaraghavan
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Abstract

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 effort 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.

Abstract Image

基于人工智能的在线教育课程预告片生成方法
在本文中,我们提出了一种基于人工智能的在线教育课程短视频形式的预告片生成方法。预告片向学习者提供课程的概述,并帮助他们对他们想要学习的课程做出明智的选择。这也有助于激发学习者的好奇心和兴趣,鼓励他们继续学习。虽然可以手动生成预告片,但它需要大量的人力和技能,涉及广泛的设计,跨度选择,视频编辑,领域知识等,因此使其既耗时又昂贵,特别是在学术环境中。我们在这项工作中提出的框架是一种基于模板的视频预告片生成方法,其中预告片的大部分文本内容是自动生成的,预告片视频是通过利用机器学习和自然语言处理技术自动生成的。建议的预告片采用时间轴的形式,由各种片段组成,这些片段是通过使用各种建议的技术选择、解释或生成内容而创建的。这些片段通过添加画外音、字幕、动画等来进一步增强,以创造一种整体体验。最后,我们使用63名人类评估员对系统生成的预告片进行了用户评估,获得了令人鼓舞的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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