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2016. On Data Driven Parametric Backchannel Synthesis for Expressing Attentiveness in Conversational Agents. Proceedings of the Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction. :43–47.
In this study, we are using a multi-party recording as a template for building a parametric speech synthesiser which is able to express different levels of attentiveness in backchannel tokens. This allowed us to investigate i) whether it is possible to express the same perceived level of attentiveness in synthesised than in natural backchannels; ii) whether it is possible to increase and decrease the perceived level of attentiveness of backchannels beyond the range observed in the original corpus.