Abstract
Abstract: Every day, countless videos are being created and shared on YouTube. and Such videos are the primary source of learning for college and school going students, people preparing for competitive exams and many more people use YouTube for productive outcomes. But longer than expected videos can be difficult to watch, and if we don't learn anything useful from them, our efforts might be in vain. Even sometimes while watching video people face lots of obstacles like network issues and all may lead to wastage of time. Automated summarization of video text allows us to quickly spot important trends and efficiently streamline the video's content, thus saving our time and efforts. In this YouTube transcript summarizer web application developed using flask, the transcript of the video is converted into text and thus summarizing that text and in case if there is no transcript available then the model will convert the audio directly into text using speech recognition followed by the summarization. Summary can be downloaded and translate in different language. Summarization of the video is done by using Python libraries and NLP (Natural Language Processing).
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