Implementing Acoustic-Prosodic Entrainment in a Conversational Avatar

Entrainment, aka accommodation or alignment, is the phenomenon by which conversational partners become more similar to each other in behavior. While there has been much work on some behaviors there has been little on entrainment in speech and even less on how Spoken Dialogue Systems which entrain to their users’ speech can be created. We present an architecture and algorithm for implementing acoustic-prosodic entrainment in SDS and show that speech produced under this algorithm conforms to the feature targets, satisfying the properties of entrainment behavior observed in human-human conversations. We present results of an extrinsic evaluation of this method, comparing whether subjects are more likely to ask advice from a conversational avatar that entrains vs. one that does not, in English, Spanish and Slovak SDS.