@inproceedings{14cff978a6e0429f82c3c2cf09e3e08a,
title = "An End-to-End Dialogue Summarization System for Sales Calls",
abstract = "Summarizing sales calls is a routine task performed manually by salespeople. We present a production system which combines generative models fine-tuned for customer-agent setting, with a human-in-the-loop user experience for an interactive summary curation process. We address challenging aspects of dialogue summarization task in a real-world setting including long input dialogues, content validation, lack of labeled data and quality evaluation. We show how GPT-3 can be leveraged as an offline data labeler to handle training data scarcity and accommodate privacy constraints in an industrial setting. Experiments show significant improvements by our models in tackling the summarization and content validation tasks on public datasets.",
author = "Abedelkadir Asi and Song Wang and Roy Eisenstadt and Dean Geckt and Yarin Kuper and Yi Mao and Royi Ronen",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022 ; Conference date: 10-07-2022 Through 15-07-2022",
year = "2022",
month = jan,
day = "1",
language = "English",
series = "NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Industry Papers",
publisher = "Association for Computational Linguistics (ACL)",
pages = "45--53",
booktitle = "NAACL 2022 - 2022 Conference of the North American Chapter of the Association for Computational Linguistics",
address = "United States",
}