Comparing Methods for Extractive Summarization of Call Centre Dialogue
September 06, 2022 ยท Declared Dead ยท ๐ Artificial Intelligence and Applications
"No code URL or promise found in abstract"
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Authors
Alexandra N. Uma, Dmitry Sityaev
arXiv ID
2209.02472
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
1
Venue
Artificial Intelligence and Applications
Last Checked
6 months ago
Abstract
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.
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