Building Autonomous Sensitive Artificial Listeners

Schröder, Marc; Bevacqua, Elisabetta; Cowie, Roddy; Eyben, Florian; Güneş, Hatice; Heylen, Dirk; Maat, Mark ter; McKeown, Gary; Pammi, Sathish; Pantić, Maja; Pélachaud, Catherine; Schuller, Björn; Sevin, Étienne de; Valstar, Michel; Wöllmer, Martin

doi:10.1109/t-affc.2011.34

Cited by 157 publications

(96 citation statements)

References 55 publications

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“…The project achieved some degree of success in these goals [4], [5]. Towards the end of the project there was an evaluation phase that involved testing the quality of interactions with the Sensitive Artificial Listeners that had been created as part of the project.…”

Section: Artificial Listenersmentioning

confidence: 99%

“…Participants interacted with each of these personalities in turn and had to evaluate the nature of the interaction. About 80 evaluation sessions were conducted in total and a final evaluation experiment involving 30 participants interacting with two versions of the system and the four characters was published [4]. The two versions of the system involved differing levels of emotional and affective signals and the final experiment showed that for some of the characters an increase in the affective signals led to improvements in levels of behavioural and felt engagement (an example interaction can be observed here [7]).…”

Section: Artificial Listenersmentioning

confidence: 99%

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Turing's menagerie: Talking lions, virtual bats, electric sheep and analogical peacocks: Common ground and common interest are necessary components of engagement

McKeown

2015

2015 International Conference on Affective Computing and Intelligent Interaction (ACII)

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Abstract-This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein's argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that-for some people at least-it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.

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Section: Artificial Listenersmentioning

confidence: 99%

Section: Artificial Listenersmentioning

confidence: 99%

Turing's menagerie: Talking lions, virtual bats, electric sheep and analogical peacocks: Common ground and common interest are necessary components of engagement

McKeown

2015

2015 International Conference on Affective Computing and Intelligent Interaction (ACII)

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show abstract

“…Similarly, the second problem may be remedied by clustering feedback (places in the speaker's speech that are followed by feedback signals from multiple listeners are more likely to contain a cue). Nevertheless, the form-features in feedback elicitation cues have proven informative enough to enable automatic detection of feedback elicitation cues in audiovisual datastreams and have been successfully used to model the feedback behaviour of virtual agents [17,20].…”

Section: Feedback Elicitationmentioning

confidence: 99%

When to Elicit Feedback in Dialogue: Towards a Model Based on the Information Needs of Speakers

Buschmeier

Kopp

2014

Intelligent Virtual Agents

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Abstract. Communicative feedback in dialogue is an important mechanism that helps interlocutors coordinate their interaction. Listeners pro-actively provide feedback when they think that it is important for the speaker to know their mental state, and speakers pro-actively seek listener feedback when they need information on whether a listener perceived, understood or accepted their message. This paper presents first steps towards a model for enabling attentive speaker agents to determine when to elicit feedback based on continuous assessment of their information needs about a user's listening state.

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“…Recently, the increase in the capabilities of incremental natural language understanding, has directed attention to the question of what type of feedback should be provided [19,24,23].…”

Section: Using Human Feedback In Human-agent Dialoguementioning

confidence: 99%

Co-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue

Buschmeier

Kopp

2013

Künstl Intell

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Grounding in dialogue concerns the question of how the gap between the individual symbol systems of interlocutors can be bridged so that mutual understanding is possible. This problem is highly relevant to human-agent interaction where mis-or non-understanding is common. We argue that humans minimise this gap by collaboratively and iteratively creating a shared conceptualisation that serves as a basis for negotiating symbol meaning. We then present a computational model that enables an artificial conversational agent to estimate the user's mental state (in terms of contact, perception, understanding, acceptance, agreement and based upon his or her feedback signals) and use this information to incrementally adapt its ongoing communicative actions to the user's needs. These basic abilities are important to reduce friction in the iterative coordination process of co-constructing grounded symbols in dialogue.

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Building Autonomous Sensitive Artificial Listeners

Abstract: International audienc

Cited by 157 publications

References 55 publications

Turing's menagerie: Talking lions, virtual bats, electric sheep and analogical peacocks: Common ground and common interest are necessary components of engagement

Turing's menagerie: Talking lions, virtual bats, electric sheep and analogical peacocks: Common ground and common interest are necessary components of engagement

When to Elicit Feedback in Dialogue: Towards a Model Based on the Information Needs of Speakers

Co-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue

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