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@article{204614,
        author = {Saiesh Kulkarni and Anant Suryawanshi and Atharv Rokade and Rushikesh Vetal and Vedant Jadhav},
        title = {Meetsum: AI-Based Multi-lingual Meeting Summarizer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {1},
        pages = {2971-2977},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204614},
        abstract = {MeetSum: Online Meeting Summarizer and Report Generation System is an Artificial Intelligence (AI)-driven web application designed to automate meeting documentation and enhance organizational productivity. The increasing volume of online meetings has created a need for efficient tools that can accurately capture, process, and summarize meeting content. The proposed system addresses this challenge by converting meeting audio and video recordings into text transcripts, generating concise summaries, extracting key discussion points, and providing multilingual translation support.The system supports both uploaded recordings and real-time meeting processing, enabling users to access structured meeting information with minimal effort. Faster-Whisper is employed for high-accuracy speech-to-text conversion, while the OpenRouter API facilitates translation and AI-based text processing tasks. Natural Language Toolkit (NLTK) is utilized for keyword extraction and text analysis, and Google Text-to-Speech (gTTS) provides audio playback functionality. The application is developed using React for the frontend, FastAPI for backend services, and MongoDB for secure data storage and management.},
        keywords = {Meeting Summarization, Speech-to-Text, Natural Language Processing, Artificial Intelligence, Faster-Whisper, OpenRouter API, FastAPI, React, MongoDB, Multilingual Translation, Report Generation.},
        month = {June},
        }