TY  - BOOK
AB  - In human dialogue, listener feedback is a pervasive phenomenon that serves important functions in the coordination of the conversation, both in regulating its flow, as well as in creating and ensuring understanding between interlocutors. This make feedback an interesting mechanism for conversational human–agent interaction. In this paper we describe computational models for an ‘attentive speaker’ agent that is able to (1) interpret the feedback behaviour of its human interlocutors by probabilistically attributing listening-related mental states to them; (2) incrementally adapt its ongoing language and behaviour generation to their needs; and (3) elicit feedback from them when needed. We present a semi-autonomous interaction study, in which we compare such an attentive speaker agent with agents that either do not adapt their behaviour to their listeners’ needs, or employ highly explicit ways of ensuring understanding. The results show that human interlocutors interacting with the attentive speaker agent provided significantly more listener feedback, felt that the agent was attentive to, and adaptive to their feedback, attested the agent a desire to be understood, and rated it more helpful in resolving difficulties in their understanding.
DA  - 2018
KW  - artificial conversational agents
KW  - attentive speaking
KW  - listener feedback
KW  - adaptation
KW  - computational modelling
KW  - interaction study
LA  - eng
PY  - 2018
TI  - Communicative listener feedback in human–agent interaction: Artificial speakers need to be attentive and adaptive
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-29169945
Y2  - 2024-11-22T01:44:19
ER  -