ISCA Archive AutoMin 2021
ISCA Archive AutoMin 2021

Team Symantlytical @ AutoMin 2021: Generating Readable Minutes with GPT-2 and BERT-based Automatic Minuting Approach

Amitesh Garg, Muskaan Singh

This paper describes our participation system run to Automatic Minuting @ Interspeech 20211. The task was motivated towards generating automatic minutes. We make a initial step towards, namely Main Task A, Task B and Task C. The main task A, was to automatically create minutes from multiparty meeting transcripts, while task B to identify whether the minute belongs to the transcript and task C. The shared task, consisting of three subtasks, required to produce, contrast and scrutinize the meeting minutes. The process of automating minuting is considered to be one of the most challenging tasks in natural language processing and sequence-to-sequence transformation. It involves testing the semantic meaningfulness, readability and reasonable adequacy of the Minutes produced in the system. In the proposed work, we have developed a system using pre-trained language models in order to generate dialogue summaries or minutes. The designed methodology considers coverage, adequacy and readability to produce the best utilizable summary of a meeting transcript with any length. Our evaluation results in subtask A achieve a score of 11% R-L which by far is the most challenging than subtask as it required systems to generate the rational minutes of the given meeting transcripts.


doi: 10.21437/AutoMin.2021-8

Cite as: Garg, A., Singh, M. (2021) Team Symantlytical @ AutoMin 2021: Generating Readable Minutes with GPT-2 and BERT-based Automatic Minuting Approach. Proc. First Shared Task on Automatic Minuting at Interspeech 2021, 65-70, doi: 10.21437/AutoMin.2021-8

@inproceedings{garg21_automin,
  author={Amitesh Garg and Muskaan Singh},
  title={{Team Symantlytical @ AutoMin 2021: Generating Readable Minutes with GPT-2 and BERT-based Automatic Minuting Approach}},
  year=2021,
  booktitle={Proc. First Shared Task on Automatic Minuting at Interspeech 2021},
  pages={65--70},
  doi={10.21437/AutoMin.2021-8}
}