The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like turn taking, politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for Social Signal Processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes a set of recommendations for enabling the development of the next generation of socially-aware computing.

The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for Social Signal Processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes aset of recommendations for enabling the development of the next generation of socially-aware computing.

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Abstract—In this paper, we proposed a new framework to incorporate an intelligent agent software robot into a crisis communication portal (CCNet) in order to send alert news to subscribed users via email and other mobile services such as Short Message Service (SMS), Multimedia Messaging Service (MMS) and General Packet Radio Services (GPRS). The content on the mobile services can be delivered either through mobile phone or Personal Digital Assistance (PDA). This research has shown that with our proposed framework, the embodied conversation agents system can handle questions intelligently with our multilayer architecture. At the same time, the extended framework can take care of delivery content through a more humanoid interface on mobile devices.

Abstract. We describe an empirical study of Marve, a virtual receptionist located at the entrance of our research laboratory. Marve engages with lab members and visitors in natural face-to-face communication, takes and delivers messages, tells knock-knock jokes, conducts natural small talk on movies, and discusses the weather. In this research, we investigate the relative popularity of Marve’s social conversational capabilities and his role-specific messaging tasks, as well as his perceived social characteristics. Results indicate that users are interested in interacting with Marve, use social conversational conventions with Marve, and perceive and describe him as a social entity. 1

Social Signal Processing (SSP) aims at the analysis of social behaviour in both Human-Human and Human-Computer interactions. SSP revolves around automatic sensing and interpretation of social signals, complex aggregates of nonverbal behaviours through which individuals express their attitudes towards other human (and virtual) participants in the current social context. As such, SSP integrates both engineering (speech analysis, computer vision, etc.) and human sciences (social psychology, anthropology, etc.) as it requires multimodal and multidisciplinary approaches. As of today, SSP is still in its early infancy, but the domain is quickly developing, and a growing number of works is appearing in the literature. This paper provides an introduction to nonverbal behaviour involved in social signals and a survey of the main results obtained so far in SSP. It also outlines possibilities and challenges that SSP is expected to face in the next years if it is to reach its full maturity.

Abstract. Software-intensive systems become more and more important in our everyday lives. But their increasing complexity makes it difficult to develop and maintain them. This chapter gives an overview of the state of the art of building software-intensive systems and outlines research challenges that have been identified by the InterLink working group “software-intensive systems and new computing paradigms”. 1

In this paper we report on a Wizard of Oz interaction study with an Embodied Conversational Agent. The agent was placed on a large display in the university crush area, an informal student meeting space over the course of a week. The main goal of the experiment was to gain information about interesting conversation topics for the students in order to inform the design of an autonomous version of the agent that can act as a long term companion in a natural social setting. We report the study results, discuss the possible reasons for the lack of meaningful conversation that the ECA could elicit from the students and report on lessons learned from this experiment.