Advanced Content and Interface Personalization through Conversational Behavior and Affective Embodied Conversational Agents

Conversation is becoming one of the key interaction modes in HMI. As a result, the conversational agents (CAs) have become an important tool in various everyday scenarios. From Apple and Microsoft to Amazon, Google, and Facebook, all have adapted their own variations of CAs. The CAs range from chatbots and 2D, carton-like implementations of talking heads to fully articulated embodied conversational agents performing interaction in various concepts. Recent studies in the field of face-to-face conversation show that the most natural way to implement interaction is through synchronized verbal and co-verbal signals (gestures and expressions). Namely, co-verbal behavior represents a major source of discourse cohesion. It regulates communicative relationships and may support or even replace verbal counterparts. It effectively retains semantics of the information and gives a certain degree of clarity in the discourse. In this chapter, we will represent a model of generation and realization of more natural machine-generated output

Neprototipni diskurzni označevalec zdaj

Prispevek predstavlja kvalitativno študijo primera diskurznega označevalca zdaj, ki je bil doslej proučevan v prozodično nevpeti strukturi oz. kot prototipni diskurzni označevalec. Strukturna, tj. prozodična, analiza kaže, da se diskurzni označevalec zdaj pojavlja tudi v neprototipni obliki. Na podlagi semantične analize, ki jo podpremo s testom parafraziranja in prevajanja, ugotavljamo, da neprototipni zdaj uvaja manjše tematske premike kot njegova prototipna različica in se pojavlja predvsem v vlogi poudarjanja, medtem ko je za prototipni zdaj značilna predvsem vloga strukturiranja diskurza. The present paper presents a qualitative case study of the Slovene discourse marker zdaj (now), which, thus far, has been explored in its prosodically prominent structure or as a prototypical discourse marker. The structural, i.e., the prosodical analysis, highlights that the discourse marker zdaj also manifests in its non-prototypical form. By means of semantic analysis, underpinned by p araphrase a nd t ranslation t ests, we s uggest t hat t he n on-prototypical form signals subtler frame shifts than its prototypical counterpart, and that it primarily functions as an emphasis device, whereas the prototypical zdaj predominately performs discourse structuring functions

Can Turn-Taking Highlight the Nature of Non-Verbal Behavior: A Case Study

The present research explores non-verbal behavior that accompanies the management of turns in naturally occurring conversations. To analyze turn management, we implemented the ISO 24617-2 multidimensional dialog act annotation scheme. The classification of the communicative intent of non-verbal behavior was performed with the annotation scheme for spontaneous authentic communication called the EVA annotation scheme. Both dialog acts and non-verbal communicative intent were observed according to their underlying nature and information exchange channel. Both concepts were divided into foreground and background expressions. We hypothesize that turn management dialog acts, being a background expression, co-occur with communication regulators, a class of non-verbal communicative intent, which are also of background nature. Our case analysis confirms this hypothesis. Furthermore, it reveals that another group of non-verbal communicative intent, the deictics, also often accompany turn management dialog acts. As deictics can be both foreground and background expressions, the premise that background non-verbal communicative intent is interlinked with background dialog acts is upheld. And when deictics were perceived as part of the foreground they co-occurred with foreground dialog acts. Therefore, dialog acts and non-verbal communicative intent share the same underlying nature, which implies a duality of the two concepts

Multilingual Chatbots to Collect Patient-Reported Outcomes

With spoken language interfaces, chatbots, and enablers, the conversational intelligence became an emerging field of research in man-machine interfaces in several target domains. In this paper, we introduce the multilingual conversational chatbot platform that integrates Open Health Connect platform and mHealth application together with multimodal services in order to deliver advanced 3D embodied conversational agents. The platform enables novel human-machine interaction with the cancer survivors in six different languages. The platform also integrates patients’ reported information as patients gather health data into digital clinical records. Further, the conversational agents have the potential to play a significant role in healthcare, from assistants during clinical consultations, to supporting positive behavior changes, or as assistants in living environments helping with daily tasks and activities