@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://aclanthology.org/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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Utilizing Large Language Models for Customized Dialogue Data Augmentation and Psychological Counseling
%A Qi, Zhiyang
%Y Inoue, Koji
%Y Fu, Yahui
%Y Axelsson, Agnes
%Y Ohashi, Atsumoto
%Y Madureira, Brielen
%Y Zenimoto, Yuki
%Y Mohapatra, Biswesh
%Y Stricker, Armand
%Y Khosla, Sopan
%S Proceedings of the 20th Workshop of Young Researchers’ Roundtable on Spoken Dialogue Systems
%D 2024
%8 September
%I Association for Computational Linguistics
%C Kyoto, Japan
%F qi-2024-utilizing
%X 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.
%U https://aclanthology.org/2024.yrrsds-1.31
%P 84-86
Markdown (Informal)
[Utilizing Large Language Models for Customized Dialogue Data Augmentation and Psychological Counseling](https://aclanthology.org/2024.yrrsds-1.31) (Qi, YRRSDS-WS 2024)
ACL