부산대학교 도서관

Politeness enhances interactions by improving relations between the participants. If there is a display of rudeness, even the finest conversation can fall through. In addition, if lathered with kindness, even the most angst-prone circumstance can be expressed with far less suffering. Previously, researchers have focused upon including politeness in conversations. But the existing research does not focus on variations in politeness according to the user profile. Therefore, in this article, we propose a novel task of generating polite personalized dialog responses in accordance with the user profile and consistent with the conversational history. We design a novel Polite Personalized Dialog Generation (PoPe-DG) framework that employs a reinforced deliberation network. We create human-annotated politeness templates according to user profiles to induce politeness variation in the generated responses for the proposed task. Precisely, the personality profile is transformed and normalized into a vector using the fusion attention combined with dialogue utterances to build context. Furthermore, the context modules and the annotated templates are appended to initialize the deliberation decoder. Experimental analysis validates that our proposed approach inculcates politeness in responses in accordance with the user profile and the conversational history.