Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues
<|reference_start|>Conversational Rubert for Detecting Competitive Interruptions in ASR-Transcribed Dialogues: 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.<|reference_end|>
@article{galimzianov2024conversational,
    title={Conversational Rubert for Detecting Competitive Interruptions in
  ASR-Transcribed Dialogues},
    author={Dmitrii Galimzianov, Viacheslav Vyshegorodtsev},
    journal={Computer Science & Information Technology (CS & IT), ISSN : 2231 -
  5403, Volume 14, Number 13, June 2024},
    year={2024},
    doi={10.5121/csit.2024.141306},
    archivePrefix={arXiv},
    eprint={2407.14940},
    primaryClass={cs.CL cs.LG cs.SD eess.AS}
}