Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues
- URL: http://arxiv.org/abs/2407.14940v1
- Date: Sat, 20 Jul 2024 17:25:53 GMT
- Title: Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues
- Authors: Dmitrii Galimzianov, Viacheslav Vyshegorodtsev,
- Abstract summary: A system that automatically classifies interruptions can be used in call centers, specifically in the tasks of customer satisfaction monitoring and agent monitoring.
We developed a text-based interruption classification model by preparing an in-house dataset consisting of ASR-transcribed customer support telephone dialogues in Russian.
- Score: 0.6138671548064356
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Interruption in a dialogue occurs when the listener begins their speech before the current speaker finishes speaking. Interruptions can be broadly divided into two groups: cooperative (when the listener wants to support the speaker), and competitive (when the listener tries to take control of the conversation against the speaker's will). A system that automatically classifies interruptions can be used in call centers, specifically in the tasks of customer satisfaction monitoring and agent monitoring. In this study, we developed a text-based interruption classification model by preparing an in-house dataset consisting of ASR-transcribed customer support telephone dialogues in Russian. We fine-tuned Conversational RuBERT on our dataset and optimized hyperparameters, and the model performed well. With further improvements, the proposed model can be applied to automatic monitoring systems.
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