VidTextBot using Generative AI

Introduction: This research paper presents the design and implementation of a VidTextBot , it is a cutting-edge system that is used to integrate the video-to-text conversion using generative AI for analyzing the video content. The system will allow the users to upload the video or the youtube link. This youtube link or the video is processed to extract the audio, transcribe it into text, and extract subtitles if available. These outputs are stored into the database for smooth future reference and efficient data retrieval. By utilizing advanced NLP models like ChatGPT, the chatBot will help the user to interact with the video content and it will also answer the real time queries. The system’s architecture ensures seamless integration of transcription, subtitle extraction and AI interaction, which contribute to make it a user-friendly platform. Objectives: VidTextBot provides a unique solution, compared to the ordinary transcription tools, which focuses on real-time capabilities and scalability. Moreover, the paper searches for potential system enhancements, such as multi-language transcription support, personalized user experiences through authentication, and optimization for mobile platforms. The future advancement can involve integrating sentiment analysis and predictive models for deeper insights into video content. VidTextBot displays the potential of video processing and Generative AI, which offers an efficient way to analyze and interpret the video data. It addresses the growing demand for tools capable of making video data more accessible, insightful, and actionable.. Methods: The VidTextBot system allows the users to upload the video or provide the youtube link for the processing. The system then extracts the audio, and then transcribes it into text. It can also extract the subtitles if any of the youtube videos have it. This information is then stored into the database for efficient retrieval and future preferences. Then the system further uses the AI generated ChatBot , so that the users can interact with the video content and get real-time answers to all of the queries. Results: The VidTextBot using the Generative-AI System is definitely a new, innovative product changing the face of interaction with video content. Combining video/audio transcription, subtitle extraction, and AI-driven chatbot capabilities, the system makes video content accessible and more user-friendly.This project is based on real-world challenges, like the long running process of analyzing videos manually and the fact that video content would be hard to derive any valuable insight. The system lets users upload any video or provide a link from YouTube, allowing its audio to be converted into text that can be queried in real-time. Integration of advanced AI guarantees users will get the correct and context-related response to their questions, thereby ensuring it becomes both practical and efficient. Conclusions: The project illustrates a huge leap in how people consume and interact with video content. It combines speech recognition and generative AI to create an efficient, interactive, and user-centric solution. A system that is indeed a huge leap forward for smarter video content analysis, making it accessible and leading the way for further advancements in the field.