Interactive Dialogue Interface for Personalized News Article Comprehension

Tomoya Higuchi, Michimasa Inaba

Abstract: We developed an interface to explain news articles through dialogue by considering the user’s comprehension level. The interface generates several pertinent questions based on the ongoing dialogue and news article, and users advance the conversation by selecting a question. Based on the user’s selected questions, the interface estimates their comprehension level of the news article and adjusts the difficulty of the generated questions accordingly. This enables a personalized dialogue tailored to each user’s comprehension needs. The results of the baseline comparison experiments confirmed the usefulness of the interface.