Team JU_PAD @ AutoMin 2021: MoM Generation from Multiparty Meeting Transcript

Abstract

Use of online meeting platforms for long multi-party discus-sion is gradually increasing and generation of Minutes of Meeting (MoM) is crucial for subsequent events. MOM records all key issues, possible solutions, decisions and actions taken dur-ing the meeting. Hence the importance of minuting cannot be overemphasized in a time when a significant number of meet-ings take place in the virtual space. Automatic generation of MoM can potentially save up to 80% of time while revisiting. In this paper, we present an abstractive approach for automatic generation of meeting minutes. It aims to deal with problems like the nature of spoken text, length of transcripts and lack of document structure and conversation fillers. The system is evaluated on a test dataset. The evaluation score is calculated by both manual and automatic systems. Text summarization metrics ROUGE-1, ROUGE-2, ROUGE-L [1] are used for automated scoring and metrics Adequacy, Grammatical Correctness, Fluency are used for manual scoring. The proposed model achieved 0.221, 0.046, 0,125 for ROUGE-1, ROUGE-2 , ROUGE-L respectively in automated evaluation and 3.5/5, 3/5, 3/5 for Adequacy, Grammatical Correctness, Fluency respectively in manual evaluation.