the outbreak of covid-19 has forced us to change the way we do things at home and at work. as the need for smooth running of online business activities continue to surge, we are looking at how we can apply our technology to meet the need. below, we would like to share an overview of our paper  presented at automin 2021. for more technical details, we invite you to read the original paper. to address the challenges mentioned above, we proposed an automatic minute generation framework that consists of segmentation, summarization, and argument mining modules.
usually, we need reference summaries to train a neural-network-based summarization model but one major advantage of our approach is that we do not need reference minutes to automatically generate summaries from transcripts. the argument mining module formulates a minute from topic-specific summarized texts, while reorganizing them so that they are consistent in structure. to compose such structures in a meeting minute, we first applied our argument mining(2) parser  which predicts an argumentative label for each sentence and the relationship between sentences. adequacy denotes whether a minute adequately captures the major topics discussed in the meeting, and grammatical correctness looks at the grammatically consistency of the minutes. figure 2 is a portion of the minutes generated with our technology and the corresponding source transcript, and shows how the automatically generated minutes are well-structured and intelligible to those involved.
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