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@article{175700,
        author = {Awez shaikh and Ansari Furqan and Mulla Mohammad Usama Zainuddin and Arshad Ahmed Anisul},
        title = {PODCAST SUMMARIZER USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {4388-4396},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175700},
        abstract = {The project titled "Podcast Summarizer using ML" aims to develop a sophisticated system that automatically generates concise and accurate summaries of spoken content in podcasts using advanced natural language processing (NLP) and machine learning techniques. The system will leverage speech-to-text technologies to transcribe audio input and employ summarization algorithms to extract the most important information, delivering coherent and informative summaries. This tool will enhance user experience by allowing listeners to quickly grasp the key points of lengthy podcasts, making the vast amount of audio content more accessible and easier to navigate. The project also addresses challenges such as handling diverse accents, varying audio quality, and ensuring summarization accuracy, providing a valuable resource for podcast enthusiasts, researchers, and content creators.},
        keywords = {Summarizer, NLP, BERT, Sentiment Analysis, Podcasts.},
        month = {April},
        }