Generating Listening Behaviour

Dirk K.J. Heylen, Elisabetta Bevacqua, Catherine Pelachaud, Isabella Poggi, Jonathan Gratch, Marc Schröder

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    24 Citations (Scopus)
    15 Downloads (Pure)

    Abstract

    In face-to-face conversations listeners provide feedback and comments at the same time as speakers are uttering their words and sentence. This ‘talk’ in the backchannel provides speakers with information about reception and acceptance – or lack thereof – of their speech. Listeners, through short verbalisations and non-verbal signals, show how they are engaged in the dialogue. The lack of incremental, real-time processing has hampered the creation of conversational agents that can respond to the human interlocutor in real time as the speech is being produced. The need for such feedback in conversational agents is, however, undeniable for reasons of naturalism or believability, to increase the efficiency of communication and to show engagement and building of rapport. In this chapter, the joint activity of speakers and listeners that constitutes a conversation is more closely examined and the work that is devoted to the construction of agents that are able to show that they are listening is reviewed. Two issues are dealt with in more detail. The first is the search for appropriate responses for an agent to display. The second is the study of how listening responses may increase rapport between agents and their human partners in conversation.
    Original languageUndefined
    Title of host publicationEmotion-oriented Systems. The Humaine Handbook
    EditorsRoddy Cowie, Catherine Pelachaud, Paolo Petta
    Place of PublicationLondon
    PublisherSpringer
    Pages321-347
    Number of pages27
    ISBN (Print)978-3-642-15183-5
    DOIs
    Publication statusPublished - 2011

    Publication series

    NameCognitive Technologies
    PublisherSpringer Verlag
    ISSN (Print)1611-2482

    Keywords

    • METIS-285107
    • IR-79615
    • EWI-21460
    • HMI-IA: Intelligent Agents
    • listening virtual humans backchannel

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