This paper is an exploration in the semantics and pragmatics of linguistic feedback, i.e., linguistic mechanisms which enable the participants in spoken interaction to exchange information about basic communicative functions, such as contact, perception, understanding, and attitudinal reactions to the communicated content. Special attention is given to the type of reaction conveyed by feedback utterances, the communicative status of the information conveyed (i. e., the level of awareness and intentionality of the communicating sender), and the context sensitivity of feedback expressions. With regard to context sensitivity, which is one of the most characteristic features of feedback expressions, the discussion focuses on the way in which the type of speech act (mood), the factual polarity and the information status of the preceding utterance influence the interpretation of feedback utterances. The different content dimensions are exemplified by data from recorded dialogues and by data given through linguistic intuition. Finally, two different ways of formalizing the analysis are examined, one using attribute-value matrices and one based on the theory of situation semantics.

This paper deals with a multimodal annotation scheme dedicated to the study of gestures in interpersonal communication, with particular regard to the role played by multimodal expressions for feedback, turn management and sequencing. The scheme has been developed under the framework of the MUMIN network and tested on the analysis of multimodal behaviour in short video clips in Swedish, Finnish and Danish. The preliminary results obtained in these studies show that the reliability of the categories defined in the scheme is acceptable, and that the scheme as a whole constitutes a versatile analysis tool for the study of multimodal communication behaviour.

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Although interaction has been acknowledged as central in value creation there is still a lack of empirical studies on how value creation is accomplished in practice, and in particular how communicative skills support customers' value creation. The purpose of this paper is therefore to generate a deeper understanding of how customer service representatives' communicative skills in conversations with customers support customers' value creation. We argue that value creating processes correspond to customers' roles as "feelers", "thinkers" and "doers". Accordingly, value creation involves three interdependent elements, an emotional, a cognitive and a behavioral. Based on a qualitative research design, drawing on an empirical study of 80 telephone conversations between customers and customer service representatives in a business-to-business context, the paper demonstrates three communicative skills that are essential in supporting customers' value creation: attentiveness, perceptiveness and responsiveness. The findings show how employees, by means of these communicative skills support customers' value creation. Attentiveness supports cognitive elements of the customers' value creating processes, whereas perceptiveness supports value creation in terms of cognitive, behavioral and emotional aspects. Finally, responsiveness supports the customer's cognitive as well as behavioral value creation.

Abstract. In natural communication, both speakers and listeners are active most of the time. While a speaker contributes new information, a listener gives feedback by producing unobtrusive (usually short) vocal or non-vocal bodily expressions to indicate whether he/she is able and willing to communicate, perceive, and understand the information, and what emotions and attitudes are triggered by this information. The simulation of feedback behavior for artificial conversational agents poses big challenges such as the concurrent and integrated perception and production of multi-modal and multi-functional expressions. We present an approach on modeling feedback for and with virtual humans, based on an approach to study "embodied feedback" as a special case of a more general theoretical account of embodied communication. A realization of this approach with the virtual human Max is described and results are presented.