AI based approach to Trailer Generation for Online Educational Courses
Prakhar Mishra, Chaitali Diwan, Srinath Srinivasa, G., Srinivasaraghavan

TL;DR
This paper presents an AI-driven, template-based system for automatically generating educational course trailers, reducing manual effort and enhancing engagement through NLP and machine learning techniques.
Contribution
The work introduces a novel automated framework for educational trailer generation that combines NLP, machine learning, and multimedia enhancements, streamlining the creation process.
Findings
User evaluations showed positive feedback on trailer quality
Automated trailers effectively conveyed course content and interest
System reduced manual effort in trailer creation
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 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…
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Taxonomy
TopicsVideo Analysis and Summarization · Virtual Reality Applications and Impacts · Educational Games and Gamification
