Towards virtual communities on the Web: Actors and audience

We report about ongoing research in a virtual reality environment where visitors can interact with agents that help them to obtain information, to perform certain transactions and to collaborate with them in order to get some tasks done. Our environment models a theatre in our hometown. We discuss attempts to let this environment evolve into a theatre community where we do not only have goal-directed visitors, but also visitors that that are not sure whether they want to buy or just want information or visitors who just want to look around. It is shown that we need a multi-user and multiagent environment to realize our goals. Since our environment models a theatre it is also interesting to investigate the roles of performers and audience in this environment. For that reason we discuss capabilities and personalities of agents. Some notes on the historical development of networked communities are included

Towards Communicating Agents and Avatars in Virtual Worlds

We report about ongoing research in a virtual reality environment where visitors can interact with agents that help them to obtain information, to perform certain transactions and to collaborate with them in order to get some tasks done. In addition, in a multi-user version of the system visitors can chat with each other. Our environment is a laboratory for research and for experiments with users interacting with agents in multimodal ways, referring to visualized information and making use of knowledge possessed by domain agents, but also by agents that represent other visitors of this environment. We discuss standards that are under development for designing such environments. Our environment models a local theatre in our hometown. We discuss our attempts to let this environment evolve into a theatre community where we do not only have goal-directed visitors buying tickets, but also visitors that that are not yet sure whether they want to buy or just want information or visitors who just want to look around, talk with others, etc. It is shown that we need a multi-user and multi-agent environment to realize our goals and that we need to have a unifying framework in order to be able to introduce and maintain different agents and user avatars with different abilities, including intellectual, interaction and animation abilities

Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition

This paper presents a self-supervised method for visual detection of the active speaker in a multi-person spoken interaction scenario. Active speaker detection is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings. The proposed method is intended to complement the acoustic detection of the active speaker, thus improving the system robustness in noisy conditions. The method can detect an arbitrary number of possibly overlapping active speakers based exclusively on visual information about their face. Furthermore, the method does not rely on external annotations, thus complying with cognitive development. Instead, the method uses information from the auditory modality to support learning in the visual domain. This paper reports an extensive evaluation of the proposed method using a large multi-person face-to-face interaction dataset. The results show good performance in a speaker dependent setting. However, in a speaker independent setting the proposed method yields a significantly lower performance. We believe that the proposed method represents an essential component of any artificial cognitive system or robotic platform engaging in social interactions.Comment: 10 pages, IEEE Transactions on Cognitive and Developmental System

Continuous Interaction with a Virtual Human

Attentive Speaking and Active Listening require that a Virtual Human be capable of simultaneous perception/interpretation and production of communicative behavior. A Virtual Human should be able to signal its attitude and attention while it is listening to its interaction partner, and be able to attend to its interaction partner while it is speaking – and modify its communicative behavior on-the-fly based on what it perceives from its partner. This report presents the results of a four week summer project that was part of eNTERFACE’10. The project resulted in progress on several aspects of continuous interaction such as scheduling and interrupting multimodal behavior, automatic classification of listener responses, generation of response eliciting behavior, and models for appropriate reactions to listener responses. A pilot user study was conducted with ten participants. In addition, the project yielded a number of deliverables that are released for public access

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

Synchronization of Speech and Gesture : Evidence for Interaction in Action

Peer reviewedPostprin

Enhancing an Eye-Tracker based Human-Computer Interface with Multi-modal Accessibility Applied for Text Entry

In natural course, human beings usually make use of multi-sensory modalities for effective communication or efficiently executing day-to-day tasks. For instance, during verbal conversations we make use of voice, eyes, and various body gestures. Also effective human-computer interaction involves hands, eyes, and voice, if available. Therefore by combining multi-sensory modalities, we can make the whole process more natural and ensure enhanced performance even for the disabled users. Towards this end, we have developed a multi-modal human-computer interface (HCI) by combining an eye-tracker with a soft-switch which may be considered as typically representing another modality. This multi-modal HCI is applied for text entry using a virtual keyboard appropriately designed in-house, facilitating enhanced performance. Our experimental results demonstrate that using multi-modalities for text entry through the virtual keyboard is more efficient and less strenuous than single modality system and also solves the Midas-touch problem, which is inherent in an eye-tracker based HCI system where only dwell time is used for selecting a character