Using Sports Videos to Showcase Exciting Content to Viewers

Abstract

In this thesis, we explore the task of generating highlight videos from sports games through the means of assessing the level of excitement of such videos to extract interesting moments from a game as well as utilize NLP techniques to generate captions for such videos. We create pipelines for the extraction of highlight clips using an audio heuristic for which we obtain transcriptions and, using a defined schema for exciting captions, fine-tune pre-trained transformer models to extract the best sentence from the video clip to use as a caption. Our results show improvements over baselines that solely use emotion-prediction categories of input sentences, suggesting our models are able to learn additional features to determine the excitement of captions.