Expectation and Reaction as Intention for Conversation System

Intention plays an import role in human daily conversation. Conventionally, human intention exerts influence on conversation contents and atmosphere. Although dialogue systems that involve emotion awareness are popular, implementation of human intention on artificial intelligence does not draw much attention of researchers. The reason is that intention is usually not a spontaneous response of external stimulus, but a self-generated desire and expectation. Moreover, internal intentions are not subjected to external signals that can be observed by third parties. In this research, we experimentally used "reaction" and "expectation" factors to represent intention at a text level and created intentional conversation model based on transformer model. Preliminary results were given to show that applying intention is able to help the a dialogue system address a higher level of engagement in the conversation.