@inproceedings{ikegami-etal-2026-dialogue,
    title = "A Dialogue Agent to Let Users Experience and Gently Enhance the ``Gyaru-Mind''",
    author = "Ikegami, Momoka  and
      Kato, Takuya  and
      Aoyagi, Saizo  and
      Hirai, Tatsunori",
    editor = "Riccardi, Giuseppe  and
      Mousavi, Seyed Mahed  and
      Torres, Maria Ines  and
      Yoshino, Koichiro  and
      Callejas, Zoraida  and
      Chowdhury, Shammur Absar  and
      Chen, Yun-Nung  and
      Bechet, Frederic  and
      Gustafson, Joakim  and
      Damnati, G{\'e}raldine  and
      Papangelis, Alex  and
      D{'}Haro, Luis Fernando  and
      Mendon{\c{c}}a, John  and
      Bernardi, Raffaella  and
      Hakkani-Tur, Dilek  and
      Di Fabbrizio, Giuseppe {''}Pino{''}  and
      Kawahara, Tatsuya  and
      Alam, Firoj  and
      Tur, Gokhan  and
      Johnston, Michael",
    booktitle = "Proceedings of the 16th International Workshop on Spoken Dialogue System Technology",
    month = feb,
    year = "2026",
    address = "Trento, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/dashboard-stats/2026.iwsds-1.14/",
    pages = "128--133",
    abstract = "In {J}apan, the term ``Gyaru-Mind'' is commonly used to describe an upbeat mindset associated with gyaru culture, often linked to proactive positivity and strong self-affirmation. While it is widely regarded as beneficial, ``Gyaru-Mind'' lacks an academic operationalization and practical method for internalization. In this work, we define a quantitative index, ``{GYARU}-{MIDX}'', built from eight text-based factors, and implement a dialogue agent named {GYARU}-{AI} that uses this index in real time. During conversation, the agent estimates a user{'}s score and produces brief, context-appropriate replies by choosing between advice and empathy, so responses are not just positive all the time. A live ``{GYARU}-{MIDX}'' view provides real-time feedback for reflection and practice. The current system is {J}apanese-only because it is trained on {J}apanese ``gyaru'' style. We describe initial design and modeling results and outline limitations and next steps."
}