Analyzing Nonverbal Listener Responses using Parallel Recordings of Multiple Listeners

In this paper we study nonverbal listener responses on a corpus with multiple parallel recorded listeners. These listeners were meant to believe that they were the sole listener, while in fact there were three persons listening to the same speaker. The speaker could only see one of the listeners. We analyze the impact of the particular setup of the corpus on the behavior and perception of the two types of listeners; the listeners that could be seen by the speaker and the listeners that could not be seen. Furthermore we compare the nonverbal listening behaviors of these three listeners to each other with regard to timing and form. We correlate these behaviors with behaviors of the speaker, like pauses and whether the speaker is looking at the listeners or not

A Survey on Evaluation Metrics for Backchannel Prediction Models

In this paper we give an overview of the evaluation metrics used to measure the performance of backchannel prediction models. Both objective and subjective evaluation metrics are discussed. The survey shows that almost every backchannel prediction model is evaluated with a different evaluation metric. This makes comparison between developed models unreliable, even beside the other variables in play, such as different corpora, language, conversational setting, amount of data and/or definition of the term backchannel

Facial displays, emotional expressions and conversational acts

“Emotional expression is multifaceted – expression is determined both by a person’s reaction to an event and by the attempt to manipulate this expression for strategic reasons in social interaction.” (Scherer, 2001). In this\ud paper we present some thoughts on the relation between emotion, facial expression and dialogue that have lead us to develop a model of dialogue in which the social views on language use are hooked up with theories of the sociology of emotions and in which facial expressions are mainly studied as discourseoriented actions without loosing track of the emotional antecedents and consequences that gave rise to them or that they raise

Investigating mind markers in design meetings

In the context of the European AMI1 project, “Augmented Multiparty Interaction” more than one hundred hours of video and audio data have been collected of groups of four people engaged in a meeting with the task to design a new remote control. The collection of meetings is being annotated on several layers, ranging from speech transcripts to emotion annotation. The main purpose of this data collection within the AMI project is to train, through machine learning techniques, automatic recognizers and interpreters of the data that would be able to deliver automatic meta-data which can be used in browsing and retrieval of new recordings. Besides this technological goal, the data collection will also be useful for the social sciences, particularly for the study of small group interactions

Perception of non-verbal emotional listener feedback

This paper reports on a listening test assessing the perception of short non-verbal emotional vocalisations emitted by a listener as feedback to the speaker. We clarify the concepts backchannel and feedback, and investigate the use of affect bursts as a means of giving emotional feedback via the backchannel. Experiments with German and Dutch subjects confirm that the recognition of emotion from affect bursts in a dialogical context is similar to their perception in isolation. We also investigate the acceptability of affect bursts when used as listener feedback. Acceptability appears to be linked to display rules for emotion expression. While many ratings were similar between Dutch and German listeners, a number of clear differences was found, suggesting language-specific affect bursts

Robotic Rabbit Companions: amusing or a nuisance?

Most of the studies in human-robot interaction involve controlled experiments in a laboratory and only a limited number of studies have put robotic companions into people’s home. Introducing robots into a real-life environment does not only pose many technical challenges but also raises several methodological issues. And even though there might be a gain in ecological validity of the findings, there are other drawbacks that limit the validity of the results. In this paper we reflect on some of these issues based on the experience we gained in the SERA project where a robotic companion was put in the homes of a few people for ten days. We try to draw some general lessons from this experience

Improvements on a simple muscle-based 3D face for realistic facial expressions

Facial expressions play an important role in face-to-face communication. With the development of personal computers capable of rendering high quality graphics, computer facial animation has produced more and more realistic facial expressions to enrich human-computer communication. In this paper, we present a simple muscle-based 3D face model that can produce realistic facial expressions in real time. We extend Waters' (1987) muscle model to generate bulges and wrinkles and to improve the combination of multiple muscle actions. In addition, we present techniques to reduce the computation burden on the muscle mode

Backchannels: Quantity, Type and Timing Matters

In a perception experiment, we systematically varied the quantity, type and timing of backchannels. Participants viewed stimuli of a real speaker side-by-side with an animated listener and rated how human-like they perceived the latter's backchannel behavior. In addition, we obtained measures of appropriateness and optionality for each backchannel from key strokes. This approach allowed us to analyze the influence of each of the factors on entire fragments and on individual backchannels. The originally performed type and timing of a backchannel appeared to be more human-like, compared to a switched type or random timing. In addition, we found that nods are more often appropriate than vocalizations. For quantity, too few or too many backchannels per minute appeared to reduce the quality of the behavior. These findings are important for the design of algorithms for the automatic generation of backchannel behavior for artificial listeners