• Tanvi Budhabaware
• Siddharth Khurangale
• Atharva Wagh
• Safal Taksale
• Dr. Shilipa Khedkar

Online meetings and remote work have grown commonplace in the wake of the COVID-19 epidemic, underscoring the importance of effective meeting minutes creation. This study investigates the use of Natural Language Processing (NLP) methods to automate the creation of meeting minutes. The two main objectives of the study are gathering meeting transcripts and producing succinct summaries. To enable additional analysis, the recorded meeting speech is converted into text using voice-to-text technology. For the purpose of producing coherent and human-like summaries, extractive and abstractive summarization techniques—including the usage of GPT models—are examined. The system's architecture combines analogue to digital conversion with speech to text processing, text generation, and data processing to produce meeting minutes that are both accurate and efficient. The research provides insights into the developments and difficulties in this area and emphasizes the value of NLP in creating meeting minutes. In the post-COVID-19 era, the suggested automated method has the potential to increase productivity and simplify the creation of meeting minutes.

Natural Language Processing, BERT, Text Summarization, GPT, Abstractive Summarization, Extractive Summarization

"Generating Minutes of the Meeting using NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.n297-n301, May-2023, Available :http://www.jetir.org/papers/JETIR2305D44.pdf

"Generating Minutes of the Meeting using NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppn297-n301, May-2023, Available at : http://www.jetir.org/papers/JETIR2305D44.pdf