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@article{169525,
        author = {Ms. Seema R. Mane and Ms. Khushbu Agrawal and Mr. Krushna Gajare and Mr. Pranav Pisal and Ms. Manasi Wagh},
        title = {Survey Paper on Automated Video Transcript Summarizer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1152-1156},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169525},
        abstract = {Nowadays, a lot of videos that provide information about various topics are posted every day. Finding the right video and comprehending its information is the main issue since, although there are many videos available, some of them contain useless content, even though we should be able to get the best content. It is a waste of time and effort to extract the correct usage full information if we are unable to find the correct one. We put out a novel concept that employs BERT Summarization for text summarization and NLP processing for text extraction. Users can distinguish between pertinent and irrelevant information based on their needs thanks to this abstractive summary and text description of the video's key content. Additionally, our trials demonstrate that the joint model may get good results in a human review using a multi-line video description and summary that is informative, succinct, and legible.},
        keywords = {Plant diseases, Crop security, infection, etc},
        month = {November},
        }