@inproceedings{qi-2024-utilizing,
    title = "Utilizing Large Language Models for Customized Dialogue Data Augmentation and Psychological Counseling",
    author = "Qi, Zhiyang",
    editor = "Inoue, Koji  and
      Fu, Yahui  and
      Axelsson, Agnes  and
      Ohashi, Atsumoto  and
      Madureira, Brielen  and
      Zenimoto, Yuki  and
      Mohapatra, Biswesh  and
      Stricker, Armand  and
      Khosla, Sopan",
    booktitle = "Proceedings of the 20th Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems",
    month = sep,
    year = "2024",
    address = "Kyoto, Japan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2024.yrrsds-1.31/",
    doi = "10.18653/v1/2024.yrrsds-1.31",
    pages = "84--86",
    abstract = "Large language models (LLMs), such as GPT-4, have driven significant technological advances in spoken dialogue systems (SDSs). In the era of LLMs, my research focuses on: (1) employing these models for customized dialogue data augmentation to improve SDS adaptability to various speaking styles, and (2) utilizing LLMs to support counselors with psychological counseling dialogues. In the future, I aim to integrate these themes, applying user adaptability to psychological counseling dialogues to facilitate smoother conversations."
}