@inproceedings{onozeki-2024-knowledge,
    title = "Knowledge-Grounded Dialogue Systems for Generating Interesting and Engaging Responses",
    author = "Onozeki, Hiroki",
    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-1.9/",
    doi = "10.18653/v1/2024.yrrsds-1.9",
    pages = "25--27",
    abstract = "My research interests lie in the area of building a dialogue system to generate interesting and entertaining responses, with a particular focus on knowledge-grounded dialogue systems. Study of open-domain dialogue systems seeks to maximize user engagement by enhancing specific dialogue skills. To achieve this goal, much research has focused on the generation of empathetic responses, personality-based responses, and knowledge-grounded responses. In addition, interesting and entertaining responses from the open-domain dialogue systems can increase user satisfaction and engagement due to their diversity and ability to attract the user{'}s interest. It has also been observed in task-oriented dialogue, user engagement can be increased by incorporating interesting responses into the dialogue. For example, methods have been proposed to incorporate interesting responses into spoken dialogue systems (SDSs) that support the execution of complex tasks and provide a pleasant and enjoyable experience for the user. However, even in the case of interesting responses, if the dialogue is incoherent, user engagement is likely to be significantly reduced. To create a dialogue system that is consistent and interesting in a dialogue context, I am working on using knowledge-grounded response generation methods to select interesting knowledge that is relevant to the dialogue context and to make responses that are based on that knowledge."
}