Beyond Conventional Recognition: Concept of a Conversational System Utilizing Metaphor Misunderstanding as a Source of Humor

Abstract

Although we are still quite far from constructing a human-like conversational system, researchers all over the world keep investigating numerous factors that make conversations between humans. In this work we focus on two such factors: humor and metaphors.Numerous research projects exist in the area of metaphor understanding and generation. We propose a unique approach to this subject, based on an observation that humans can not only properly understand and generate metaphors, but also make fun of their misunderstandings. For instance, an utterance "you have legs like a deer" can be understood as a compliment ("long and graceful"), as well as an insult ("very hairy"). If used properly, such misunderstanding can serve as source of humor in human-computer conversations.Currently we are working on constructing a large scale metaphor conceptual network, in which links between concepts are calculated accordingly to their roles in metaphor understanding. When finished, the network should make it possible for the computer to understand and generate metaphors, and, consequently, also misunderstand (or act as if it misunderstood) them. In this paper we propose a design of a conversational system utilizing these mechanisms. We also consider using emotion-from-text detector to improve aptness of generated misunderstandings.