Developing a Production System for Purpose of Call Detection in Business Phone Conversations

Elena Khasanova, Pooja Hiranandani, Shayna Gardiner, Cheng Chen, Simon Corston-Oliver, Xue-Yong Fu


Abstract
For agents at a contact centre receiving calls, the most important piece of information is the reason for a given call. An agent cannot provide support on a call if they do not know why a customer is calling. In this paper we describe our implementation of a commercial system to detect Purpose of Call statements in English business call transcripts in real time. We present a detailed analysis of types of Purpose of Call statements and language patterns related to them, discuss an approach to collect rich training data by bootstrapping from a set of rules to a neural model, and describe a hybrid model which consists of a transformer-based classifier and a set of rules by leveraging insights from the analysis of call transcripts. The model achieved 88.6 F1 on average in various types of business calls when tested on real life data and has low inference time. We reflect on the challenges and design decisions when developing and deploying the system.
Anthology ID:
2022.naacl-industry.29
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track
Month:
July
Year:
2022
Address:
Hybrid: Seattle, Washington + Online
Editors:
Anastassia Loukina, Rashmi Gangadharaiah, Bonan Min
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
259–267
Language:
URL:
https://aclanthology.org/2022.naacl-industry.29
DOI:
10.18653/v1/2022.naacl-industry.29
Bibkey:
Cite (ACL):
Elena Khasanova, Pooja Hiranandani, Shayna Gardiner, Cheng Chen, Simon Corston-Oliver, and Xue-Yong Fu. 2022. Developing a Production System for Purpose of Call Detection in Business Phone Conversations. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, pages 259–267, Hybrid: Seattle, Washington + Online. Association for Computational Linguistics.
Cite (Informal):
Developing a Production System for Purpose of Call Detection in Business Phone Conversations (Khasanova et al., NAACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.naacl-industry.29.pdf
Video:
 https://aclanthology.org/2022.naacl-industry.29.mp4