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Über dieses Buch

This volume presents a collection of research studies on sophisticated and functional computational instruments able to recognize, process, and store relevant situated interactional signals, as well as, interact with people, displaying reactions (under conditions of limited time) that show abilities of appropriately sensing and understanding environmental changes, producing suitable, autonomous, and adaptable responses to various social situations. These social robotic autonomous systems will improve the quality of life of their end-users while assisting them on several needs, ranging from educational settings, health care assistance, communicative disorders, and any disorder impairing either their physical, cognitive, or social functional activities. The multidisciplinary themes presented in the volume will be interesting for experts and students coming from different research fields and with different knowledge and backgrounds. The research reported is particularly relevant for academic centers, and Research & Development Institutions.



Chapter 1. Moving Robots from Industrial Sectors to Domestic Spheres: A Foreword

This foreword analyses how in the shift from industrial sectors to social and domestic sectors the form of robots is actually subjected to great changes. Furthermore, it reports some recent data on robot diffusion, implicitly inviting researchers to reflect on the trends of robot diffusion that give the precise indication to focus on the material sphere of the housework.
Leopoldina Fortunati

Chapter 2. Modeling Social Signals and Contexts in Robotic Socially Believable Behaving Systems

There is a need for a holistic perspective when considering aspects of natural interactions with robotic socially believable behaving systems, that must account of the cultural, social, physical, and individual (the context) features that shape interactional exchanges. Context (the physical, social and organizational context) rules individual’s social conducts and provide means to render the world sensible and interpretable in the course of everyday activities. Contextual aspects of interactional exchanges make any of it unique and requiring different interpretations and actions. A robotic socially believable system must be able to discriminate among the infinities of contextual instances and assign to each their unique meaning. This book reports on the last research efforts in making “natural” human interactional exchanges with social robotic autonomous systems devoted to improve the quality of life of their end-users while assisting them on several needs, ranging from educational settings, health care assistance, communicative disorders, and any disorder impairing either their physical, cognitive, or social functional activities.
Anna Esposito, Lakhmi C. Jain

Chapter 3. Adaptive and Evolutive Algorithms: A Natural Logic for Artificial Mind

This paper focuses on one of the biggest challenges we face: the possibility of reproducing in an artificial agent (based on formal algorithms) some typically human capacities (based on natural logic algorithms) such as consciousness, the ability to deliberate and make moral judgments. Recent evidences arising from dynamic systems theory and statistical learning, from the psychobiology of development and molecular neuroscience are overcoming some of the fundamental assumptions of artificial intelligence and the cognitive science of the last 50 years. From the molecular level to the social one, these new approaches analyze and exploit the structure of complex causal systems physically incorporated and integrated with the environment, setting the stage for the emergence of organisms capable of adaptive flexibility and intelligent behavior.
Mauro Maldonato, Silvia Dell’Orco

Chapter 4. Toward Conscious-Like Conversational Agents

Although considerable effort has been already devoted to studying various aspects of human-machine interaction, we are still a long way from developing socially believable conversational agents. This paper identifies some of the main causes of the current state in the field: (i) socially believable behaviour of a technical system is misinterpreted as a functional requirement, rather than a qualitative, (ii) the currently prevalent statistical approaches cannot address research problems of managing human-machine interaction that require some sort of contextual analysis, and (iii) the structure of human-machine interaction is unjustifiably reduced to a task structure. In addition, we propose a way to address these pitfalls. We consider the capability of a technical system to simulate fundamental features of human consciousness as one of the key desiderata to perform socially believable behaviour. In line with this, the paper discusses the possibilities for the computational realization of (iv) unified interpretation, (v) learning through interaction, and (vi) context-dependent perception in the context of human-machine interaction.
Milan Gnjatović, Branislav Borovac

Chapter 5. Communication Sequences and Survival Analysis

Two new methods of analyzing dialogue interactions are outlined. One method depends on abstract representations of dialogue events as symbols in a formal language. This method invites analysis of the expressivity requirements of dialogue grammar, as well as distribution analysis of dialogue event symbol sequences. The method is presented in relation to a temporal construction from regular languages, one which supports increasingly fine granularity of temporal analysis. The other method proposed is also temporally oriented. It also depends on dialogue events and dialogue states, and proposes to analyze causal relations among dialogue events through survival analysis. These methods are suggested as additions to the extant repertoire of approaches to understanding the structure and temporal flow of natural dialogue. Additional methods of analysis of natural dialogue may contribute to deeper understanding of the phenomena. With deeper undertanding of natural dialogue one may hope to more fully inform the construction of believable artificial systems that are intended to engage in dialogue with a manner close to human interaction in dialogue.
Carl Vogel

Chapter 6. The Relevance of Context and Experience for the Operation of Historical Sound Change

This paper is concerned with explaining how historical sound change can emerge as a consequence of the association between continuous, dynamic speech signals and phonological categories. The relevance of this research to developing socially believable speech processing machines is that sound change is both cognitive and social and also because it provides a unique insight into how the categories of speech and language and dynamic speech signals are inter-connected. A challenge is to understand how unstable conditions that can lead to sound change are connected with the more typical stable conditions in which sound change is minimal. In many phonetic models of sound change, stability and instability come about because listeners typically parse—very occasionally misparse—overlapping articulatory movements in a way that is consistent with their production. Experience-based models give greater emphasis to how interacting individuals can bring about sound change at the population level. Stability in these models is achieved through reinforcing in speech production the centroid of a probability distribution of perceived episodes that give rise to a phonological category; instability and change can be brought about under various conditions that cause different category distributions to shift incrementally and to come into contact with each other. Beyond these issues, the natural tendency to imitation in speech communication may further incrementally contribute to sound change both over adults’ lifespan and in the blending of sounds that can arise through dialect contact. The general conclusion is that the instabilities that give rise to sound change are an inevitable consequence of the same mechanisms that are deployed in maintaining the stability between phonological categories and their association with the speech signal.
Jonathan Harrington, Felicitas Kleber, Ulrich Reubold, Mary Stevens

Chapter 7. Fostering User Engagement in Face-to-Face Human-Agent Interactions: A Survey

Embodied conversational agents are capable of carrying a face-to-face interaction with users. Their use is substantially increasing in numerous applications ranging from tutoring systems to ambient assisted living. In such applications, one of the main challenges is to keep the user engaged in the interaction with the agent. The present chapter provides an overview of the scientific issues underlying the engagement paradigm, including a review on methodologies for assessing user engagement in human-agent interaction. It presents three studies that have been conducted within the Greta/VIB platforms. These studies aimed at designing engaging agents using different interaction strategies (alignment and dynamical coupling) and the expression of interpersonal attitudes in multi-party interactions.
Chloé Clavel, Angelo Cafaro, Sabrina Campano, Catherine Pelachaud

Chapter 8. Virtual Coaches for Healthy Lifestyle

Since the introduction of the idea of the software interface agent the question recurs whether these agents should be personified and graphically visualized in the interface. In this chapter we look at the use of virtual humans in the interface of healthy lifestyle coaching systems. Based on theory of persuasive communication we analyse the impact that the use of graphical interface agents may have on user experience and on the efficacy of this type of persuasive systems. We argue that research on the impact of a virtual human interface on the efficacy of these systems requires longitudinal field studies in addition to the controlled short-term user evaluations in the field of human computer interaction (HCI). We introduce Kristina, a mobile personal coaching system that monitors its user’s physical activity and that presents feedback messages to the user. We present results of field trials (\(\text {N}=60\), 7 weeks) in which we compare two interface conditions on a smartphone. In one condition feedback messages are presented by a virtual animated human, in the other condition they are displayed on the screen in text. Results of the field trials show that user motivation, use context and the type of device on which the feedback message is received influence the perception of the presentation format of feedback messages and the effect on compliance to the coaching regime.
H. J. A. op den Akker, R. Klaassen, A. Nijholt

Chapter 9. Social Perception in Machines: The Case of Personality and the Big-Five Traits

Research agendas aimed at the development of socially believable behaving systems often indicate automatic social perception as one of the steps. However, the exact meaning of the word “perception” seems still to be unclear in the computing community, in particular when it applies to social and psychological phenomena that are not accessible to direct observation. This chapter tries to shed light on the problem by showing examples of approaches that perform Automatic Personality Perception, i.e. the prediction of personality traits that people attribute to others.
Alessandro Vinciarelli

Chapter 10. Towards Modelling Multimodal and Multiparty Interaction in Educational Settings

This paper presents an experimental design and setup that explores the interaction between two children and their tutor during a question–answer session of a reading comprehension task. The multimodal aspects of the interactions are analysed in terms of preferred signals and strategies that speakers employ to carry out successful multi-party conversations. This analysis will form the basis for the development of behavioral models accounting for the specific context. We envisage the integration of such models into intelligent, context-aware systems, i.e. an embodied dialogue system that has the role of a tutor and is able to carry out a discussion in a multiparty setting by exploring the multimodal signals of the children. This system will have the ability to discuss a text and address questions to the children, encouraging collaboration and equal participation in the discussion and assessing the answers that the children give. The paper focuses on the design of the appropriate setup, the data collection and the analysis of the multimodal signals that are important for the realization of such a system.
Maria Koutsombogera, Miltos Deligiannis, Maria Giagkou, Harris Papageorgiou

Chapter 11. Detecting Abnormal Behavioral Patterns in Crowd Scenarios

This Chapter presents a framework for the the task of abnormality detection in crowded scenes based on the analysis of trajectories, build up upon a novel video descriptor, called Histogram of Oriented Tracklets. Unlike standard approaches that employ low level motion features, e.g. optical flow, to form video descriptors, we propose to exploit mid-level features extracted from long-range motion trajectories called tracklets, which have been successfully applied for action modeling and video analysis. Following standard procedure, a video sequence is divided into spatio-temporal cuboids within which we collect statistics of the tracklets passing through them. Specifically, tracklets orientation and magnitude are quantized in a two-dimensional histogram which encodes the actual motion patterns in each cuboid. These histograms are then fed into machine learning models (e.g., Latent Dirichlet allocation and Support Vector Machines) to detect abnormal behaviors in video sequences. The evaluation of the proposed descriptor on different datasets, namely UCSD, BEHAVE, UMN and Violence in Crowds, yields compelling results in abnormality detection, by setting new state-of-the-art and outperforming former descriptors based on the optical flow, dense trajectories and social force models.
Hossein Mousavi, Hamed Kiani Galoogahi, Alessandro Perina, Vittorio Murino


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