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Business Meeting Summarisation System

EasyChair Preprint no. 8043

6 pagesDate: May 22, 2022


As the economy expands, so does the quantity of production and sales in a firm; as a result, a substantial number of business meetings are conducted day-to-day to make crucial choices. The importance of business meetings cannot be overstated. It enables you to maintain track of the organization’s processes and operations to achieve the organization’s goals and objectives. The business meeting findings must be kept up to dateby a large number of individuals. Conventionally, people had to read long meeting reports or talk to meeting attendees to get the gist of the meeting. This summarization tool helps the user to gain the information shared in a meeting with just one click. It can be used in various domains like education, healthcare, business, etc. Existing summarization systems are limited to only English language. This work demonstrates summarizing a business meeting held in regional or professional languages with the help of a machine learning model. The summarization is done using the abstractive method wherein words are allocated based on their frequency of occurrence in the text file. The machine learning model is connected to the NodeJS server application with the help of a python connecter. To overcome the current barriers, this system takes audio input of Hindi or English language from the user end, summarizes it using ML techniques which improve overall accuracy and provide the output in any desired language.

Keyphrases: Abstractive Summarization, Artificial Intelligence., Audio summarization, Natural Language Processing

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Pallavi Lodhi and Shubhangi Kharche and Dikshita Kambri and Sumaiya Khan},
  title = {Business Meeting Summarisation System},
  howpublished = {EasyChair Preprint no. 8043},

  year = {EasyChair, 2022}}
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