This book explores the use of technology to detect, predict and understand social cues, in order to analyze and prevent conflict. Traditional human sciences approaches are enriched with the latest developments in Social Signal Processing aimed at an automatic understanding of conflict and negotiation. Communication-both verbal and non-verbal, within the context of a conflict-is studied with the aim of promoting the use of intelligent machines that automatically measure and understand the escalation of conflict, and are able to manage it, in order to support the negotiation process. Particular attention is paid to the integration of human sciences findings with computational approaches, from the application of correct methodologies for the collection of valid data to the development of computational approaches inspired by research on verbal and multimodal communication. In the words of the trade unionist Pierre Carniti, "We should reevaluate conflict, since without conflict there is no social justice." With this in mind, this volume does not approach conflict simply as an obstacle to be overcome, but as a concept to be fully analyzed. The philosophical, linguistic and psychological aspects of conflict, once understood, can be used to promote conflict management as a means for change and social justice.

This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

This book constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Multimodal Communication in Political Speech: Shaping Minds and Social Actions, held in Rome, Italy, during November 10-12, 2010. The 16 regular papers were carefully reviewed and selected from 33 submissions and presented with three key-notes. The purpose of the Political Speech workshops is to provide a forum for discussing research areas of persuasive agents and social signal processing. This book covers topics on multimodal aspects of political communication, including persuasion, fallacies, racist discourse, as well as music, autobiographic memories, metonymies, dominant postures, rhetorical strategies, interruptions, intonation, and voice appeal.

This book constitutes refereed proceedings of the COST 2102 International Training School on Cognitive Behavioural Systems held in Dresden, Germany, in February 2011. The 39 revised full papers presented were carefully reviewed and selected from various submissions. The volume presents new and original research results in the field of human-machine interaction inspired by cognitive behavioural human-human interaction features. The themes covered are on cognitive and computational social information processing, emotional and social believable Human-Computer Interaction (HCI) systems, behavioural and contextual analysis of interaction, embodiment, perception, linguistics, semantics and sentiment analysis in dialogues and interactions, algorithmic and computational issues for the automatic recognition and synthesis of emotional states.

This volume brings together the advanced research results obtained by the European COST Action 2102 "Cross Modal Analysis of Verbal and Nonverbal Communication," primarily discussed at the PINK SSPnet-COST2102 International Conference on Analysis of Verbal and Nonverbal Communication and Enactment: The Processing Issues, held in Budapest, Hungary, in September 2010. The 40 papers presented were carefully reviewed and selected for inclusion in the book. The volume is arranged into two scientific sections. The first section, Multimodal Signals: Analysis, Processing and Computational Issues, deals with conjectural and processing issues of defining models, algorithms, and heuristic strategies for data analysis, coordination of the data flow and optimal encoding of multi-channel verbal and nonverbal features. The second section, Verbal and Nonverbal Social Signals, presents original studies that provide theoretical and practical solutions to the modelling of timing synchronization between linguistic and paralinguistic expressions, actions, body movements, activities in human interaction and on their assistance for an effective human-machine interactions.

Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.