NLP Driven Ensemble Based Automatic Subtitle Generation and Semantic Video Summarization Technique
This addresses efficient storage and quick browsing of large video collections for users in big data contexts, but it appears incremental as it builds on existing text summarization and ensemble techniques.
The paper tackled automatic subtitle generation and semantic video summarization by using speech recognition and NLP-based text summarization algorithms, enhanced with ensemble methods like intersection and weight-based learning, reporting satisfactory performance results.
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