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Aspect-based meeting transcript summarization aims to produce multiplesummaries, each focusing on one aspect of content in a meeting transcript. Itis challenging as sentences related to different aspects can mingle together,and those relevant to a specific aspect can be scattered throughout the longtranscript of a meeting. The traditional summarization methods produce onesummary mixing information of all aspects, which cannot deal with the abovechallenges of aspect-based meeting transcript summarization. In this paper, wepropose a two-stage method for aspect-based meeting transcript summarization.To select the input content related to specific aspects, we train a sentenceclassifier on a dataset constructed from the AMI corpus with pseudo-labeling.Then we merge the sentences selected for a specific aspect as the input for thesummarizer to produce the aspect-based summary. Experimental results on the AMIcorpus outperform many strong baselines, which verifies the effectiveness ofour proposed method.

Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification