'You are Sooo Cool, Valentina!' Recognizing Social Attitude in Speech-Based Dialogues with an ECA

We propose a method to recognize the `social attitude' of users towards an Embodied Conversational Agent (ECA) from a combination of linguistic and prosodic features. After describing the method and the results of applying it to a corpus of dialogues collected with a Wizard of Oz study, we discuss the advantages and disadvantages of statistical and machine learning methods if compared with other knowledge-based methods.

• Type: Conference
• Year: 2007
• Where: ACII
• Authors: Fiorella de Rosis, Anton Batliner, Nicole Novielli, Stefan Steidl
• Keywords: ACII 2007, Applied Computing, Embodied Conversational Agent, Machine Learning Methods, Social Attitude