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[3O1-OS-2c-01] Investigation of a Dialogue System with User Model Estimation Function using a Large-Scale Language Model
Keywords:semantic network, personalization, large-scale language model, dialogue system
The purpose of this study is to estimate user models for personalized dialogue systems. We consider a method for estimating user models from dialogues using a large-scale language model (GPT-3). Based on the information obtained from the dialogues, a large-scale language model is controlled by prompts to acquire and update user models. User models expressed in sentences are converted into the form of a network. We constructed a dialogue system and verified the effectiveness of the user model acquisition method and the quality of the dialogue.
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