Capturing Form of Non-verbal Conversational Behavior for Recreation on Synthetic Conversational Agent EVA

Several features of human-human conversation have to be accounted for in order to recreate conversational behavior on a synthetic model, as natural as possible.. Spontaneous conversations are a combination of multiple modalities (e.g. gestures, postures, gazes, expressions) in order to effectively convey information between participants. This paper presents a novel process for capturing the forms of motion performed during spontaneous conversations. Furthermore, it also addresses the process of transforming the captured motions’ descriptions into high-resolution, expressively transformable behavioral scripts. The aim of the research was design a process that will allow building a highresolution motion dictionary. The dictionary is to be presented as a set of expressively transformable behavioral scripts, each capturing the expressive details from a spontaneous conversation (e.g. spatial, repetitive, structural, and temporal features). Key-Words: multimodal annotation, conversational behavior, high-resolution annotation, motion dictionary, analysis of non-verbal behavior