Adapting the backchanneling behaviour of a social robot to increase user engagement : A study using social robots with contingent backchanneling behaviour

Sammanfattning: There are many aspects of human communication that affects the nature of an interaction; examples include voice intonation and facial expressions. A particular type of verbal and non-verbal cues, so called backchannels, have an underlying role in shaping conversations. In this study we analyse how backchannels can affect engagement of two participants engaged in a task with a social robot. Furthermore, given the ever increasing interest in using social robots in service contexts, we analyse the current level of customer acceptance for social robots and which aspects the participants think is important when interacting with one in a service setting using interviews. The social robot produces contingent backchannels based on engagement levels to increase the participation of the least speaking participant. An interview was conducted after the experiment to analyse the participants attitudes towards the use of social robots in services. 40 people participated in pairs of two, where each pair was assigned to either the experimental or the control condition. In the experimental condition the backchannels were targeted towards the least dominant speaker and in the control setting the backchannels were randomly generated. Each pair consisted of one native speaker and one language learner of Swedish. The results showed that in the experimental condition the least dominant speaker increased their speech, as well as evening out the participation. The interviews showed mixed attitudes towards the use of social robots in service with some expressing hesitancy regarding the robots ability to understand speaker’s desire.