Extractive Summarization of Call Transcripts

TL;DR

This paper introduces a novel extractive summarization method for call transcripts that combines topic modeling, sentence selection, and punctuation restoration to produce more readable summaries of phone conversations.

Contribution

The paper presents an indigenous method integrating topic modeling and punctuation restoration specifically designed for call transcript summarization.

Findings

Demonstrated improved readability of summaries

Validated effectiveness through extensive testing and evaluation

Outperformed existing summarization approaches

Abstract

Text summarization is the process of extracting the most important information from the text and presenting it concisely in fewer sentences. Call transcript is a text that involves textual description of a phone conversation between a customer (caller) and agent(s) (customer representatives). This paper presents an indigenously developed method that combines topic modeling and sentence selection with punctuation restoration in condensing ill-punctuated or un-punctuated call transcripts to produce summaries that are more readable. Extensive testing, evaluation and comparisons have demonstrated the efficacy of this summarizer for call transcript summarization.