Aspect-based meeting transcript summarization aims to produce multiple summaries, each focusing on one aspect of content in a meeting transcript. It is challenging as sentences related to different aspects can mingle together, and those relevant to a specific aspect can be scattered throughout the long transcript of a meeting. The traditional summarization methods produce one summary mixing information of all aspects, which cannot deal with the above challenges of aspect-based meeting transcript summarization. In this paper, we propose a two-stage method for aspect-based meeting transcript summarization. To select the input content related to specific aspects, we train a sentence classifier 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 the summarizer to produce the aspect-based summary. Experimental results on the AMI corpus outperform many strong baselines, which verifies the effectiveness of our proposed method.

翻译：基于方面的会议记录摘要旨在生成多个摘要，每个摘要聚焦于会议记录中某个方面的内容。这一任务具有挑战性，因为涉及不同方面的句子可能相互交织，而与特定方面相关的句子可能分散在长篇会议记录中。传统的摘要方法生成一个混合所有方面信息的摘要，无法应对基于方面会议记录摘要的上述挑战。本文提出了一种用于基于方面会议记录摘要的两阶段方法。为了选择与特定方面相关的输入内容，我们在AMI语料库上通过伪标签构建的数据集上训练了一个句子分类器。然后，我们将为特定方面选择的句子合并作为摘要器的输入，以生成基于方面的摘要。在AMI语料库上的实验结果优于许多强基线，验证了我们提出方法的有效性。