Proactive Spoken Dialogue Interaction in Multi-Party Environments describes spoken dialogue systems that act as independent dialogue partners in the conversation with and between users. The resulting novel characteristics such as proactiveness and multi-party capabilities pose new challenges on the dialogue management component of such a system and require the use and administration of an extensive dialogue history. In order to assist the proactive spoken dialogue systems development, a comprehensive data collection seems mandatory and may be performed in a Wizard-of-Oz environment. Such an environment builds also the appropriate basis for an extensive usability and acceptance evaluation. Proactive Spoken Dialogue Interaction in Multi-Party Environments is a useful reference for students and researchers in speech processing.
"This book identifies the emerging research areas in Human Computer Interaction and discusses the current state of the art in these areas"--Provided by publisher.
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 book constitutes the proceedings of the 19th International Conference on Speech and Computer, SPECOM 2017, held in Hatfield, UK, in September 2017. The 80 papers presented in this volume were carefully reviewed and selected from 150 submissions. The papers present current research in the area of computer speech processing (recognition, synthesis, understanding etc.) and related domains (including signal processing, language and text processing, computational paralinguistics, multi-modal speech processing, human-computer interaction).
This volume constitutes the proceedings of the 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015, held Bilbao, Spain, June 2014. The 60 papers published in this volume were carefully reviewed and selected from 190 submissions. They are organized in topical sections such as data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications; classification and cluster analysis, HAIS applications.
The two-volume set LNCS 8547 and 8548 constitutes the refereed proceedings of the 14th International Conference on Computers Helping People with Special Needs, ICCHP 2014, held in Paris, France, in July 2014. The 132 revised full papers and 55 short papers presented were carefully reviewed and selected from 362 submissions. The papers included in the first volume are organized in the following topical sections: accessible media; digital content and media accessibility; 25 years of the Web: weaving accessibility; towards e-inclusion for people with intellectual disabilities; the impact of PDF/UA on accessible PDF; accessibility of non-verbal communication; emotions for accessibility (E4A), games and entertainment software; accessibility and therapy; implementation and take-up of e-accessibility; accessibility and usability of mobile platforms for people with disabilities and elderly persons; portable and mobile platforms for people with disabilities and elderly persons; people with cognitive disabilities: At, ICT and AAC; autism: ICT and AT; access to mathematics, science and music and blind and visually impaired people: AT, HCI and accessibility.
To create truly effective human-centric ambient intelligence systems both engineering and computing methods are needed. This is the first book to bridge data processing and intelligent reasoning methods for the creation of human-centered ambient intelligence systems. Interdisciplinary in nature, the book covers topics such as multi-modal interfaces, human-computer interaction, smart environments and pervasive computing, addressing principles, paradigms, methods and applications. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal, speech and video processing, multi-modal interfaces, human-computer interaction and applications of ambient intelligence. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University, USA. His research is on user-centric vision applications in smart homes, assisted living / well being, smart meetings, and avatar-based social interactions. He is Editor-in-Chief of "Journal of Ambient Intelligence and Smart Environments", has chaired ACM/IEEE ICDSC 2008, and organized workshops/sessions/tutorials at ECCV, ACM MM, FG, ECAI, ICASSP, CVPR. Juan Carlos Augusto is a Lecturer at the University of Ulster, UK. He is conducting research on Smart Homes and Classrooms. He has given tutorials at IJCAI’07 and AAAI’08. He is Editor-in-Chief of the Book Series on "Ambient Intelligence and Smart Environments" and the "Journal of Ambient Intelligence and Smart Environments". He has co-Chaired ICOST’06, AITAmI’06/07/08, and is Workshops Chair for IE’09. Ramón López-Cózar Delgado is a Professor at the Faculty of Computer Science and Telecommunications of the University of Granada, Spain. His research interests include speech recognition and understanding, dialogue management and Ambient Intelligence. He is a member of ISCA (International Speech Communication Association), SEPLN (Spanish Society on Natural Language Processing) and AIPO (Spanish Society on HCI). Integrates engineering and computing methods that are essential for designing and implementing highly effective ambient intelligence systems Contains contributions from the world’s leading experts in academia and industry Gives a complete overview of the principles, paradigms and applications of human-centric ambient intelligence systems
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.
This book constitutes the refereed proceedings of the 10th Congress of the Italian Association for Artificial Intelligence, AI*IA 2007. Coverage includes knowledge representation and reasoning, multiagent systems, distributed AI, knowledge engineering, ontologies and the semantic Web, machine learning, natural language processing, information retrieval and extraction, AI and robotics, AI and expressive media, and intelligent access to multimedia information.
