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arXiv · 2407.14940

Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues

Dmitrii Galimzianov·Viacheslav Vyshegorodtsev
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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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Dmitrii Galimzianov, Viacheslav Vyshegorodtsev. 2024-07-20. Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues. https://doi.org/10.5121/csit.2024.141306

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