Author
Listed:
- Ritu Kushwaha
- Sneha
- Naman Choudhary
- Vansh Sharma
- Kapil Dev Sharma
Abstract
Meetings are essential for communication, teamwork, and decision-making in today’s organizations. However, manually documenting meeting minutes takes a lot of time and often leads to errors, resulting in incomplete or inaccurate records. With the rise of virtual meetings, there is an increasing need for automated solutions to capture and summarize discussions efficiently. This paper introduces an AI-Based Meeting Minute Generator, a smart system that automates the creation of structured meeting minutes from audio or text inputs. The system uses advanced Speech Recognition techniques to turn spoken language into text and applies Natural Language Processing (NLP) to extract key insights like summaries, important discussion points, and action items. It integrates transformer-based models for summarization, keyword extraction methods, and Named Entity Recognition (NER) to identify relevant entities. Additionally, the system includes security features like malware detection and supports processing large files, making it more efficient and scalable than existing tools. This solution boosts productivity, ensures accuracy, and cuts down on manual effort. It can effectively serve corporate meetings, educational settings, and online collaboration platforms.
Suggested Citation
Ritu Kushwaha & Sneha & Naman Choudhary & Vansh Sharma & Kapil Dev Sharma, 2026.
"AI-Based Meeting Minute Generator A Review Article,"
International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 13(2), pages 907-913, April.
Handle:
RePEc:etm:ijsrst:v13:y2026:i2:id:1540
DOI: 10.32628/IJSRST2613376
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