Perceptual evaluation of backchannel strategies for artificial listeners

    Research output: Contribution to journalArticleAcademicpeer-review

    8 Citations (Scopus)

    Abstract

    Artificial listeners are virtual agents that can listen attentively to a human speaker in a dialog. In this paper, we present two experiments where we investigate the perception of rule-based backchannel strategies for artificial listeners. In both, we collect subjective judgements of humans who observe a video of a speaker together with a corresponding animation of an artificial listener. In the first experiment, we evaluate six rule-based strategies that differ in the types of features (e.g. prosody, gaze) they consider. The ratings are given at the level of a speech turn and can be considered a measure for how human-like the generated listening behavior is perceived. In the second experiment, we systematically investigate the effect of the quantity, type and timing of backchannels within the discourse of the speaker. Additionally, we asked human observers to press a button whenever they thought a generated backchannel occurrence was inappropriate. Both experiments together give insights in the factors, both from an observation and generation point-of-view, that influence the perception of backchannel strategies for artificial listeners.
    Original languageUndefined
    Pages (from-to)235-253
    Number of pages19
    JournalAutonomous agents and multi-agent systems
    Volume27
    Issue number2
    DOIs
    Publication statusPublished - Sep 2013

    Keywords

    • EC Grant Agreement nr.: FP7/231287
    • EC Grant Agreement nr.: FP7/211486
    • EWI-23302
    • HMI-IA: Intelligent Agents
    • IR-86110
    • perception study
    • Backchannel
    • Artificial Listener
    • METIS-297621
    • Listening Behavior

    Cite this

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    title = "Perceptual evaluation of backchannel strategies for artificial listeners",
    abstract = "Artificial listeners are virtual agents that can listen attentively to a human speaker in a dialog. In this paper, we present two experiments where we investigate the perception of rule-based backchannel strategies for artificial listeners. In both, we collect subjective judgements of humans who observe a video of a speaker together with a corresponding animation of an artificial listener. In the first experiment, we evaluate six rule-based strategies that differ in the types of features (e.g. prosody, gaze) they consider. The ratings are given at the level of a speech turn and can be considered a measure for how human-like the generated listening behavior is perceived. In the second experiment, we systematically investigate the effect of the quantity, type and timing of backchannels within the discourse of the speaker. Additionally, we asked human observers to press a button whenever they thought a generated backchannel occurrence was inappropriate. Both experiments together give insights in the factors, both from an observation and generation point-of-view, that influence the perception of backchannel strategies for artificial listeners.",
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    Perceptual evaluation of backchannel strategies for artificial listeners. / Poppe, Ronald Walter; Truong, Khiet Phuong; Heylen, Dirk K.J.

    In: Autonomous agents and multi-agent systems, Vol. 27, No. 2, 09.2013, p. 235-253.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AU - Poppe, Ronald Walter

    AU - Truong, Khiet Phuong

    AU - Heylen, Dirk K.J.

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    AB - Artificial listeners are virtual agents that can listen attentively to a human speaker in a dialog. In this paper, we present two experiments where we investigate the perception of rule-based backchannel strategies for artificial listeners. In both, we collect subjective judgements of humans who observe a video of a speaker together with a corresponding animation of an artificial listener. In the first experiment, we evaluate six rule-based strategies that differ in the types of features (e.g. prosody, gaze) they consider. The ratings are given at the level of a speech turn and can be considered a measure for how human-like the generated listening behavior is perceived. In the second experiment, we systematically investigate the effect of the quantity, type and timing of backchannels within the discourse of the speaker. Additionally, we asked human observers to press a button whenever they thought a generated backchannel occurrence was inappropriate. Both experiments together give insights in the factors, both from an observation and generation point-of-view, that influence the perception of backchannel strategies for artificial listeners.

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