@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://aclanthology.org/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."
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<abstract>In Japan, 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 Japanese-only because it is trained on Japanese “gyaru” style. We describe initial design and modeling results and outline limitations and next steps.</abstract>
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%0 Conference Proceedings
%T A Dialogue Agent to Let Users Experience and Gently Enhance the “Gyaru-Mind”
%A Ikegami, Momoka
%A Kato, Takuya
%A Aoyagi, Saizo
%A Hirai, Tatsunori
%Y Riccardi, Giuseppe
%Y Mousavi, Seyed Mahed
%Y Torres, Maria Ines
%Y Yoshino, Koichiro
%Y Callejas, Zoraida
%Y Chowdhury, Shammur Absar
%Y Chen, Yun-Nung
%Y Bechet, Frederic
%Y Gustafson, Joakim
%Y Damnati, Géraldine
%Y Papangelis, Alex
%Y D’Haro, Luis Fernando
%Y Mendonça, John
%Y Bernardi, Raffaella
%Y Hakkani-Tur, Dilek
%Y Di Fabbrizio, Giuseppe ”Pino”
%Y Kawahara, Tatsuya
%Y Alam, Firoj
%Y Tur, Gokhan
%Y Johnston, Michael
%S Proceedings of the 16th International Workshop on Spoken Dialogue System Technology
%D 2026
%8 February
%I Association for Computational Linguistics
%C Trento, Italy
%F ikegami-etal-2026-dialogue
%X In Japan, 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 Japanese-only because it is trained on Japanese “gyaru” style. We describe initial design and modeling results and outline limitations and next steps.
%U https://aclanthology.org/2026.iwsds-1.14/
%P 128-133
Markdown (Informal)
[A Dialogue Agent to Let Users Experience and Gently Enhance the "Gyaru-Mind"](https://aclanthology.org/2026.iwsds-1.14/) (Ikegami et al., IWSDS 2026)
ACL