NLP Driven Ensemble Based Automatic Subtitle Generation and Semantic Video Summarization Technique

TL;DR

This paper introduces an NLP-based ensemble approach for automatic subtitle generation and semantic video summarization, enhancing efficiency in video data management through speech recognition and text summarization techniques.

Contribution

It presents a novel ensemble method combining multiple text summarization algorithms for improved subtitle and video summary generation.

Findings

Ensemble methods improve subtitle accuracy and summarization quality.

The proposed technique performs satisfactorily in experimental evaluations.

Both intersection and weight-based approaches enhance summarization performance.

Abstract

This paper proposes an automatic subtitle generation and semantic video summarization technique. The importance of automatic video summarization is vast in the present era of big data. Video summarization helps in efficient storage and also quick surfing of large collection of videos without losing the important ones. The summarization of the videos is done with the help of subtitles which is obtained using several text summarization algorithms. The proposed technique generates the subtitle for videos with/without subtitles using speech recognition and then applies NLP based Text summarization algorithms on the subtitles. The performance of subtitle generation and video summarization is boosted through Ensemble method with two approaches such as Intersection method and Weight based learning method Experimental results reported show the satisfactory performance of the proposed method