Selecting appropriate agent responses based on non-content features

Mark ter Maat, Dirk K.J. Heylen

    Research output: Contribution to conferencePaperpeer-review

    2 Citations (Scopus)

    Abstract

    This paper describes work-in-progress on a study to create models of responses of virtual agents that are selected only based on non-content features, such as prosody and facial expressions. From a corpus of human-human interactions, in which one person was playing the part of an agent and the second person a user, we extracted the turns of the user and gave these to annotators. The annotators had to select utterances from a list of phrases in the repertoire of our agent that would be a good response to the user utterance. The corpus is used to train response selection models based on automatically extracted features and on human annotations of the user-turns.
    Original languageUndefined
    Pages33-36
    Number of pages4
    DOIs
    Publication statusPublished - Oct 2010
    Event3rd International Workshop on Affective Interaction in Natural Environments, AFFINE 2010 - Firenze, Italy
    Duration: 25 Oct 201029 Oct 2010

    Workshop

    Workshop3rd International Workshop on Affective Interaction in Natural Environments, AFFINE 2010
    Period25/10/1029/10/10
    Other25-29 October 2010

    Keywords

    • HMI-CI: Computational Intelligence
    • IR-79593
    • Machine Learning
    • EC Grant Agreement nr.: FP7/211486
    • Virtual agents
    • EWI-21411
    • HMI-MI: MULTIMODAL INTERACTIONS
    • Behaviour selection

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