Text-Based Detection of On-Hold Scripts in Contact Center Calls

• URL: http://arxiv.org/abs/2407.09849v1
• Date: Sat, 13 Jul 2024 11:11:41 GMT
• Title: Text-Based Detection of On-Hold Scripts in Contact Center Calls
• Authors: Dmitrii Galimzianov, Viacheslav Vyshegorodtsev,
• Abstract summary: Average hold time is a concern for call centers because it affects customer satisfaction. This study presents a natural language processing model that detects on-hold phrases in customer service calls transcribed by automatic speech recognition technology.
• Score: 0.6138671548064356
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Average hold time is a concern for call centers because it affects customer satisfaction. Contact centers should instruct their agents to use special on-hold scripts to maintain positive interactions with clients. This study presents a natural language processing model that detects on-hold phrases in customer service calls transcribed by automatic speech recognition technology. The task of finding hold scripts in dialogue was formulated as a multiclass text classification problem with three mutually exclusive classes: scripts for putting a client on hold, scripts for returning to a client, and phrases irrelevant to on-hold scripts. We collected an in-house dataset of calls and labeled each dialogue turn in each call. We fine-tuned RuBERT on the dataset by exploring various hyperparameter sets and achieved high model performance. The developed model can help agent monitoring by providing a way to check whether an agent follows predefined on-hold scripts.

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