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@article{206384,
        author = {Nitin Sugare and Dr. Sushil Venkatesh Kulkarni},
        title = {AI-Powered Online Meeting Summary Generator Using Speech Recognition and Large Language Models},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {1198-1201},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206384},
        abstract = {This paper presents the design and implementation of an AI-powered online meeting summary generator that automates transcription, summarization, and report generation from virtual meetings. Artificial Intelligence (AI) has emerged as a powerful solution for automating meeting transcription, summarization, and documentation. The system combines browser-based audio capture, speech recognition, natural language processing, and large language model-based summarization to generate concise meeting reports with minimal manual effort. The proposed architecture utilizes the Web Audio API for audio acquisition, Mozilla DeepSpeech for speech-to-text conversion, and the Gemma language model for abstractive summarization and action-item extraction. The implementation focuses on privacy-aware processing, real-time usability, and support for modern collaboration platforms. Experimental observations demonstrate that the proposed approach significantly reduces manual note-taking effort while producing structured summaries suitable for professional documentation.},
        keywords = {Online Meeting Summarization, Speech Recognition, DeepSpeech, Large Language Models, Gemma, Natural Language Processing, Web Audio API, Artificial Intelligence.},
        month = {July},
        }