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
翻译:本文建议采用自动字幕生成和语义视频汇总技术。在目前大数据时代,自动视频汇总的重要性是巨大的。视频汇总有助于高效存储和快速浏览大量视频收藏,而不会失去重要视频。视频汇总是在利用几种文本汇总算法获得字幕帮助下完成的。拟议技术通过语音识别生成带字幕/不带字幕的视频字幕字幕字幕字幕,然后在字幕中应用基于NLP的文本汇总算法。通过综合方法,如跨部门方法和基于体重的学习方法,提高了字幕生成和视频汇总的功能。据报告,实验结果显示,拟议方法的绩效令人满意。