A Model of Attention and Interest Using Gaze Behavior

Peters, Christopher J.; Pélachaud, Catherine; Bevacqua, Elisabetta; Mancini, Maurizio; Poggi, Isabella

doi:10.1007/11550617_20

Cited by 81 publications

(51 citation statements)

References 16 publications

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“…The duties of grounding in dialogue fulfilled by verbal feedback (Clark 1996;Clark and Schaefer 1989) are shared with head gestures and other nonvocal behaviour. Additionally, head movements, by co-occurrence with mutual gaze (Peters et al 2005) and correlation with other active listening displays, emphasise the degree of listener involvement in conversation. By means of head gestures, the listener can also encourage the speaker to stay active during his or her speech at turn relevance places Heldner et al 2013).…”

Section: Listener Feedback In Spontaneous Interactionmentioning

confidence: 99%

The ALICO corpus: analysing the active listener

Malisz

Włodarczak

Buschmeier

et al. 2016

Lang Resources & Evaluation

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The ALICO corpus: analysing the active listener. Abstract The Active Listening Corpus (ALICO) is a multimodal data set of spontaneous dyadic conversations in German with diverse speech and gestural annotations of both dialogue partners. The annotations consist of short feedback expression transcriptions with corresponding communicative function interpretations as well as segmentations of interpausal units, words, rhythmic prominence intervals and vowel-to-vowel intervals. Additionally, ALICO contains head gesture annotations of both interlocutors. The corpus contributes to research on spontaneous human-human interaction, on functional relations between modalities, and timing variability in dialogue. It also provides data that differentiates between distracted and attentive listeners. We describe the main characteristics of the corpus and briefly present the most important results obtained from analyses in recent years.

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Section: Listener Feedback In Spontaneous Interactionmentioning

confidence: 99%

The ALICO corpus: analysing the active listener

Malisz

Włodarczak

Buschmeier

et al. 2016

Lang Resources & Evaluation

View full text Add to dashboard Cite

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“…Previous research has highlighted the importance of gaze in monitoring attention and understanding toward achieving procedural grounding in collaboration [15,41]. The excerpt below illustrates how collaborators might use gaze to assess understanding, where the instructor monitors the student after issuing an instruction:…”

Section: Theme 2: Establishing Procedural Grounding Using Gazementioning

confidence: 99%

How social cues shape task coordination and communication

Sauppé

Mutlu

2014

Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work &Amp; Social Computing

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To design computer-supported collaborative work (CSCW) systems that effectively support remote collaboration, designers need a better understanding of how people collaborate face-to-face and the mechanisms that they use to coordinate their actions. While research in CSCW has studied how specific social cues might facilitate collaboration in specific tasks, such as the role of gestures in video instruction, less is known about how a range of communicative cues might facilitate activities across many collaborative settings. In this paper, we model the predictive relationships between facial, gestural, and vocal cues and collaborative outcomes in three different tasks, drawing conclusions on how each cue might contribute to these outcomes in a given task and how such relationships generalize across tasks. The resulting models provide a quantitative understanding of the relative importance of each type of social cue in predicting collaborative outcomes, as well as a more thorough understanding of how the role of each social cue changes across tasks. Additionally, our results provide confirmation and illumination of prior findings in face-to-face and computer-mediated communication research.

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“…The gaze behavior of our agents is informed by empirically founded gaze models [4,8,12]. [4] analyzed gaze behavior based on twoperson dialogs and found that gaze is used to regulate the exchange between the speaker and listener.…”

Section: Related Researchmentioning

confidence: 99%

“…And they also provide the needed information for our gaze generation rules. The work in [8] developed a model of attention and interest based on gaze behavior. An embodied conversational agent may start, maintain, and end a conversation dependent on its perception of the interests of the other agents.…”

Section: Related Researchmentioning

confidence: 99%

Automated generation of non-verbal behavior for virtual embodied characters

Breitfuss

Prendinger

Ishizuka

2007

Proceedings of the 9th International Conference on Multimodal Interfaces

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In this paper we introduce a system that automatically adds different types of non-verbal behavior to a given dialogue script between two virtual embodied agents. It allows us to transform a dialogue in text format into an agent behavior script enriched by eye gaze and conversational gesture behavior. The agents' gaze behavior is informed by theories of human face-to-face gaze behavior. Gestures are generated based on the analysis of linguistic and contextual information of the input text. The resulting annotated dialogue script is then transformed into the Multimodal Presentation Markup Language for 3D agents (MPML3D), which controls the multi-modal behavior of animated life-like agents, including facial and body animation and synthetic speech. Using our system makes it very easy to add appropriate non-verbal behavior to a given dialogue text, a task that would otherwise be very cumbersome and time consuming.

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A Model of Attention and Interest Using Gaze Behavior

Cited by 81 publications

References 16 publications

The ALICO corpus: analysing the active listener

The ALICO corpus: analysing the active listener

How social cues shape task coordination and communication

Automated generation of non-verbal behavior for virtual embodied characters

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