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Project Name: AI-Powered Meeting Summarizer and Task Assigner
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Project Abstract In the era of remote work and online meetings, it's often challenging to keep track of all the discussions and tasks assigned during a meeting. This project aims to develop an AI-powered project that records and analyzes online meetings on platforms like Zoom and Google Meet. The project will automatically generate a summary of the meeting and send emails to the participants with their respective tasks based on the discussion. By leveraging Natural Language Processing and Machine Learning techniques, the project will help users remember important details from the meetings and ensure that all tasks are clearly communicated and remembered. This project has the potential to significantly improve productivity and communication in remote teams.
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Project requisites: Basic knowledge of AI and machine learning, proficiency in a programming language (like Python), familiarity with cloud services, and experience with development and collaboration tools, AI,ML using Python and it's Libraries with the collaboration and Development of tools
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Novelty of the project: The novelty of this project lies in its application of AI to the problem of managing and summarizing online meetings. While there are existing solutions for recording and transcribing meetings, our project goes a step further by analyzing the content of the meetings, extracting key points, assigning tasks, and generating a summary. This not only saves time but also ensures that no important details are missed.
5.References (in IEEE reference format):
1. Shah, M., & Patel, D. (2023). Efficient meeting insights: NLP-Enhanced summarization of voice and Text. Retrieved from https://www.researchgate.net/profile/Manan-Shah-44/publication/376621969_Efficient_meeting_insights_NLP_-Enhanced_summarization_of_voice_and_Text/links/658188813c472d2e8e707105/Efficient-meeting-insights-NLP-Enhanced-summarization-of-voice-and-Text.pdf
2. O'Donovan, P. (2023). An investigation into the use of NLP to extract meeting action items for project management. Retrieved from https://norma.ncirl.ie/id/eprint/6262
3. Chen, H., & Rangarajan, S. (2023). A novel approach to summarizing business meeting transcripts. Retrieved from https://dl.acm.org/doi/abs/10.1145/3474085.3478556
4. Kumar, A., & Srinivas, T. (2023). Leveraging AI for effective meeting summarization. Retrieved from https://ieeexplore.ieee.org/abstract/document/9777155/