AI based approach to Trailer Generation for Online Educational Courses
- URL: http://arxiv.org/abs/2301.03957v1
- Date: Tue, 10 Jan 2023 13:33:08 GMT
- Title: AI based approach to Trailer Generation for Online Educational Courses
- Authors: Prakhar Mishra, Chaitali Diwan, Srinath Srinivasa, G.
Srinivasaraghavan
- Abstract summary: The framework we propose is a template based method for video trailer generation.
The proposed trailer is in the form of a timeline consisting of various fragments created by selecting, para-phrasing or generating content.
We perform user evaluation with 63 human evaluators for evaluating the trailers generated by our system.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- 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 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.
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