Zara Returns: Improved Personality Induction and Adaptation by an Empathetic Virtual Agent
Farhad Bin Siddique, Onno Pepijn Kampman, Yang Yang, Anik Dey, Pascale Fung · 2017
Virtual agents need to adapt their personality to the user in order to become more empathetic.To this end, we developed Zara the Supergirl, an interactive empathetic agent, using a modular approach.In this paper, we describe the enhanced personality module with improved recognition from speech and text using deep learning frameworks.From raw audio, an average F-score of 69.6 was obtained from realtime personality assessment using a Convolutional Neural Network (CNN) model.From text, we improved personality recognition results with a CNN model on top of pre-trained word embeddings and obtained an average F-score of 71.0.Results from our Human-Agent Interaction study confirmed our assumption that people have different agent personality preferences.We use insights from this study to adapt our agent to user personality.