Clipify: A Novel Approach to Summarize YouTube Video using LSA

doi:10.23940/ijpe.24.10.p2.602609

Abstract

Abstract:

Video summarization, a critical task in managing the ever-growing volume of digital video content, has witnessed significant advancements with the integration of Natural Language Processing (NLP) techniques. In this paper, a unique technique is provided to NLP-based video summarising that makes use of textual metadata to improve the relevance and coherence of the summaries that are produced. With the proliferation of internet videos across platforms like YouTube, Instagram, etc., there is a growing need for effective summarization methods to condense diverse content. Its primary objective is to create brief and precise video summaries of YouTube content. The proposed method initially condenses YouTube video transcripts, forming the basis for generating the summarized video. Additionally, an android application is developed to facilitate user interaction. This application enables users to input a YouTube video link. Upon successful processing, the summarized video output is generated and showcased on the application. As the volume of online video content continues to surge, efficient summarization techniques become increasingly vital for users to quickly grasp essential information and navigate through the vast array of available material. This paper's methodology not only addresses this growing demand but also offers a user-friendly interface for easy access and utilization of the summarization tool. The NLP-driven video summarization system achieved high-quality summaries, demonstrating improved coherence, relevance, and informativeness compared to traditional methods.

Key words: YouTube, video summarization, natural language processing, transcription, latent semantic analysis algorithm

Singh Yogendra, Kumar Rishu, and Kabdal Soumya. Clipify: A Novel Approach to Summarize YouTube Video using LSA [J]. Int J Performability Eng, 2024, 20(10): 602-609.

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