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@article{206292,
        author = {Nitin Sugare and Dr. Sushil Venkatesh Kulkarni},
        title = {AI-Based Meeting Documentation Systems: A Comprehensive Review of Speech Recognition and Summarization Technologies},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {2},
        pages = {880-884},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206292},
        abstract = {The growth of remote collaboration platforms has transformed the way organizations communicate, coordinate projects, and make decisions. However, documenting online meetings remains a challenging and time-consuming activity. Artificial Intelligence (AI) has emerged as a powerful solution for automating meeting transcription, summarization, and documentation. This review paper presents a comprehensive study of AI-powered online meeting summary generation systems, focusing on speech recognition, natural language processing, transformer-based architectures, large language models, and browser-based deployment approaches. The paper reviews recent research contributions, analyzes technologies such as Web Audio API, DeepSpeech, and Gemma-based language models, and discusses their application in real-time meeting intelligence systems. A detailed examination of system architecture, data flow, implementation modules, benefits, limitations, and research gaps is provided. The study concludes that intelligent meeting assistants can significantly improve productivity, reduce manual effort, and enhance organizational knowledge management.},
        keywords = {},
        month = {July},
        }