In this book, a novel approach that combines speech-based emotion recognition with adaptive human-computer dialogue modeling is described. With the robust recognition of emotions from speech signals as their goal, the authors analyze the effectiveness of using a plain emotion recognizer, a speech-emotion recognizer combining speech and emotion recognition, and multiple speech-emotion recognizers at the same time. The semi-stochastic dialogue model employed relates user emotion management to the corresponding dialogue interaction history and allows the device to adapt itself to the context, including altering the stylistic realization of its speech. This comprehensive volume begins by introducing spoken language dialogue systems and providing an overview of human emotions, theories, categorization and emotional speech. It moves on to cover the adaptive semi-stochastic dialogue model and the basic concepts of speech-emotion recognition. Finally, the authors show how speech-emotion recognizers can be optimized, and how an adaptive dialogue manager can be implemented. The book, with its novel methods to perform robust speech-based emotion recognition at low complexity, will be of interest to a variety of readers involved in human-computer interaction.

Introducing Spoken Dialogue Systems into Intelligent Environments outlines the formalisms of a novel knowledge-driven framework for spoken dialogue management and presents the implementation of a model-based Adaptive Spoken Dialogue Manager(ASDM) called OwlSpeak. The authors have identified three stakeholders that potentially influence the behavior of the ASDM: the user, the SDS, and a complex Intelligent Environment (IE) consisting of various devices, services, and task descriptions. The theoretical foundation of a working ontology-based spoken dialogue description framework, the prototype implementation of the ASDM, and the evaluation activities that are presented as part of this book contribute to the ongoing spoken dialogue research by establishing the fertile ground of model-based adaptive spoken dialogue management. This monograph is ideal for advanced undergraduate students, PhD students, and postdocs as well as academic and industrial researchers and developers in speech and multimodal interactive systems.

By providing students with the opportunities to receive a high quality education regardless of their social or cultural background, inclusive education is a new area that goes beyond traditional integration approaches. These approaches hope to provide the educative system with the ability to adapt to the diversity of its students. Technologies for Inclusive Education: Beyond Traditional Integration Approaches introduces the basic concepts, current research guidelines and future perspectives on the current state of these approaches. This book aims to make inclusive education a reality in the future by highlighting technological advances in applied e-learning, cognitive learning and education multimedia. Novel approaches to human-computer interaction are essential to make these contents available for every student regardless of their disabilities and learning styles.

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use. Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer more natural and robust interactions. This work provides insights, lessons and inspiration for future research and development, not only for spoken dialog systems, but for data-driven approaches to human-machine interaction in general.

This volume includes proceedings articles presented at the Workshop on Paralinguistic Information and its Integration in Spoken Dialogue Systems held in Granada, Spain. The material focuses on the three broad areas of spoken dialogue systems for robotics, emotions and spoken dialogue systems, and Spoken dialogue systems for real-world applications The workshop proceedings are part of the 3rd Annual International Workshop on Spoken Dialogue Systems, which brings together researchers from all over the world working in the field of spoken dialogue systems. It provides an international forum for the presentation of research and applications, and for lively discussions among researchers as well as industrialists.

Emotions and Affect in Human Factors and Human–Computer Interaction is a complete guide for conducting affect-related research and design projects in H/F and HCI domains. Introducing necessary concepts, methods, approaches, and applications, the book highlights how critical emotions and affect are to everyday life and interaction with cognitive artifacts. The text covers the basis of neural mechanisms of affective phenomena, as well as representative approaches to Affective Computing, Kansei Engineering, Hedonomics, and Emotional Design. The methodologies section includes affect induction techniques, measurement techniques, detection and recognition techniques, and regulation models and strategies. The application chapters discuss various H/F and HCI domains: product design, human–robot interaction, behavioral health and game design, and transportation. Engineers and designers can learn and apply psychological theories and mechanisms to account for their affect-related research and can develop their own domain-specific theory. The approach outlined in this handbook works to close the existing gap between the traditional affect research and the emerging field of affective design and affective computing. - Provides a theoretical background of affective sciences - Demonstrates diverse affect induction methods in actual research settings - Describes sensing technologies, such as brain–computer interfaces, facial expression detection, and more - Covers emotion modeling and its application to regulation processes - Includes case studies and applied examples in a variety of H/F and HCI application areas - Addresses emerging interdisciplinary areas including Positive Technology, Subliminal Perception, Physiological Computing, and Aesthetic Computing

The Handbook consists of four major sections. Each section is introduced by a main article: Theories of Emotion – General Aspects Perspectives in Communication Theory, Semiotics, and Linguistics Perspectives on Language and Emotion in Cultural Studies Interdisciplinary and Applied Perspectives The first section presents interdisciplinary emotion theories relevant for the field of language and communication research, including the history of emotion research. The second section focuses on the full range of emotion-related aspects in linguistics, semiotics, and communication theories. The next section focuses on cultural studies and language and emotion; emotions in arts and literature, as well as research on emotion in literary studies; and media and emotion. The final section covers different domains, social practices, and applications, such as society, policy, diplomacy, economics and business communication, religion and emotional language, the domain of affective computing in human-machine interaction, and language and emotion research for language education. Overall, this Handbook represents a comprehensive overview in a rich, diverse compendium never before published in this particular domain.