[4Xin2] Poster session 2

[4Xin2-102] Dynamic Slot-Making-and-Filling Method for Improving Long-term Dialogue Consistency

〇Keigo Komada¹, Kaori Abe^2,3, Shoji Moriya¹, Jun Suzuki^1,3 (1.Tohoku University, 2.Machine Learning Solutions Inc., 3.RIKEN)

Keywords:Dialogue, GPT, Slot-filling

Maintaining coherence in utterances over an extended period is challenging in dialogue systems, even with current technology. In scenarios where tasks can be predefined, an approach known as ``Slot (Dialogue State)'' has been proposed to enhance long-term coherence. This involves predefining slots for necessary task-related items and updating these slots' values as the conversation progresses. The objective of this study is to propose a method for maintaining long-term coherence in situations where it is challenging to align with changes in the dialogue context, such as role-playing in vocational training or tabletop role-playing games (TRPG), which conventional methods find difficult to address.
In this research, we focus on TRPG game masters and create a system utilizing GPT's output as external dynamic slots. We demonstrate the effectiveness of this approach. Results indicate the proposed method's superiority in terms of agreement with human evaluation.