A Novel Approach to Video Summarization Using AI-GPT and Speech Recognition

In an era where online video data is exploding, there is a growing need for efficient ways to summarize video content. In this paper, a novel approach is proposed that leverages AI and speech recognition techniques for video summarization. The procedure involves two main stages: audio processing and text generation. Speech recognition transcribes the video audio into text in the audio processing stage. Then, the transcribed text is fed into AI-GPT to generate a concise summary that captures the main ideas and concepts of the video in the text generation stage. Experimental results reveal considerable gains in video summarization over state-of-the-art techniques, proving the usefulness of the suggested strategy. The system is evaluated on diverse datasets, including news broadcasts, educational videos, political speeches, and sports matches that outperform other methods in terms of summary quality and processing speed. The proposed approach has potential applications in news aggregation, education, video retrieval, and video recommendation systems. It is a promising solution for addressing the difficulties of managing and analyzing large amounts of video data.