Comparing Methods for Extractive Summarization of Call Centre Dialogue
This work addresses the problem of generating call summaries for contact centre solutions, but it is incremental as it evaluates existing methods without introducing new techniques.
The paper compared extractive summarization methods for call centre dialogues, finding that TopicSum and Lead-N outperformed others in both objective (ROUGE-L) and subjective evaluations, while BERTSum scored lower.
This paper provides results of evaluating some text summarisation techniques for the purpose of producing call summaries for contact centre solutions. We specifically focus on extractive summarisation methods, as they do not require any labelled data and are fairly quick and easy to implement for production use. We experimentally compare several such methods by using them to produce summaries of calls, and evaluating these summaries objectively (using ROUGE-L) and subjectively (by aggregating the judgements of several annotators). We found that TopicSum and Lead-N outperform the other summarisation methods, whilst BERTSum received comparatively lower scores in both subjective and objective evaluations. The results demonstrate that even such simple heuristics-based methods like Lead-N ca n produce meaningful and useful summaries of call centre dialogues.