An ECA expressing appreciations

In this paper, we propose a computational model that provides an Embodied Conversational Agent (ECA) with the ability to generate verbal other-repetition (repetitions of some of the words uttered in the previous user speaker turn) when interacting with a user in a museum setting. We focus on the generation of other-repetitions expressing emotional stances in appreciation sentences. Emotional stances and their semantic features are selected according to the user´s verbal input, and ECA´s utterance is generated according to these features. We present an evaluation of this model through users´ subjective reports. Results indicate that the expression of emotional stances by the ECA has a positive effect oIn this paper, we propose a computational model that provides an Embodied Conversational Agent (ECA) with the ability to generate verbal other-repetition (repetitions of some of the words uttered in the previous user speaker turn) when interacting with a user in a museum setting. We focus on the generation of other-repetitions expressing emotional stances in appreciation sentences. Emotional stances and their semantic features are selected according to the user´s verbal input, and ECA´s utterance is generated according to these features. We present an evaluation of this model through users´ subjective reports. Results indicate that the expression of emotional stances by the ECA has a positive effect on user engagement, and that ECA´s behaviours are rated as more believable by users when the ECA utters other-repetitions.n user engagement, and that ECA´s behaviours are rated as more believable by users when the ECA utters other-repetitions.