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Author: Alexander Schmitt
Publisher: Springer Science & Business Media
ISBN: 1461445922
Category : Technology & Engineering
Languages : en
Pages : 258
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Book Description
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.
Author: Alexander Schmitt
Publisher: Springer Science & Business Media
ISBN: 1461445922
Category : Technology & Engineering
Languages : en
Pages : 258
Get Book Here
Book Description
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.
Author: Oliver Lemon
Publisher: Springer Science & Business Media
ISBN: 1461448026
Category : Computers
Languages : en
Pages : 184
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Book Description
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Author: Verena Rieser
Publisher: Springer Science & Business Media
ISBN: 3642249426
Category : Computers
Languages : en
Pages : 261
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Book Description
The past decade has seen a revolution in the field of spoken dialogue systems. As in other areas of Computer Science and Artificial Intelligence, data-driven methods are now being used to drive new methodologies for system development and evaluation. This book is a unique contribution to that ongoing change. A new methodology for developing spoken dialogue systems is described in detail. The journey starts and ends with human behaviour in interaction, and explores methods for learning from the data, for building simulation environments for training and testing systems, and for evaluating the results. The detailed material covers: Spoken and Multimodal dialogue systems, Wizard-of-Oz data collection, User Simulation methods, Reinforcement Learning, and Evaluation methodologies. The book is a research guide for students and researchers with a background in Computer Science, AI, or Machine Learning. It navigates through a detailed case study in data-driven methods for development and evaluation of spoken dialogue systems. Common challenges associated with this approach are discussed and example solutions are provided. This work provides insights, lessons, and inspiration for future research and development – not only for spoken dialogue systems in particular, but for data-driven approaches to human-machine interaction in general.
Author: Kristina Jokinen
Publisher: Springer Nature
ISBN: 3031021347
Category : Computers
Languages : en
Pages : 151
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Book Description
Considerable progress has been made in recent years in the development of dialogue systems that support robust and efficient human-machine interaction using spoken language. Spoken dialogue technology allows various interactive applications to be built and used for practical purposes, and research focuses on issues that aim to increase the system's communicative competence by including aspects of error correction, cooperation, multimodality, and adaptation in context. This book gives a comprehensive view of state-of-the-art techniques that are used to build spoken dialogue systems. It provides an overview of the basic issues such as system architectures, various dialogue management methods, system evaluation, and also surveys advanced topics concerning extensions of the basic model to more conversational setups. The goal of the book is to provide an introduction to the methods, problems, and solutions that are used in dialogue system development and evaluation. It presents dialogue modelling and system development issues relevant in both academic and industrial environments and also discusses requirements and challenges for advanced interaction management and future research. Table of Contents: Preface / Introduction to Spoken Dialogue Systems / Dialogue Management / Error Handling / Case Studies: Advanced Approaches to Dialogue Management / Advanced Issues / Methodologies and Practices of Evaluation / Future Directions / References / Author Biographies
Author: Michael F. McTear
Publisher: Springer Science & Business Media
ISBN: 0857294148
Category : Computers
Languages : en
Pages : 431
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Book Description
Spoken Dialogue Technology provides extensive coverage of spoken dialogue systems, ranging from the theoretical underpinnings of the study of dialogue through to a detailed look at a number of well-established methods and tools for developing spoken dialogue systems. The book enables students and practitioners to design and test dialogue systems using several available development environments and languages, including the CSLU toolkit, VoiceXML, SALT, and XHTML+ voice. This practical orientation is usually available otherwise only in reference manuals supplied with software development kits. The latest research in spoken dialogue systems is presented along with extensive coverage of the most relevant theoretical issues and a critical evaluation of current research prototypes. A dedicated web site containing supplementary materials, code, links to resources will enable readers to develop and test their own systems (). Previously such materials have been difficult to track down, available only on a range of disparate web sites and this web site provides a unique and useful reference source which will prove invaluable.
Author: Judy Kay
Publisher: Springer
ISBN: 3709124905
Category : Computers
Languages : en
Pages : 382
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Book Description
User modeling researchers look for ways of enabling interactive software systems to adapt to their users-by constructing, maintaining, and exploiting user models, which are representations of properties of individual users. User modeling has been found to enhance the effectiveness and/or usability of software systems in a wide variety of situations. Techniques for user modeling have been developed and evaluated by researchers in a number of fields, including artificial intelligence, education, psychology, linguistics, human-computer interaction, and information science. The biennial series of International Conferences on User Modeling provides a forum in which academic and industrial researchers from all of these fields can exchange their complementary insights on user modeling issues. The published proceedings of these conferences represent a major source of information about developments in this area.
Author: Elisabeth Andre
Publisher: Springer Science & Business Media
ISBN: 3540221433
Category : Computers
Languages : en
Pages : 336
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Book Description
Human conversational partners are able, at least to a certain extent, to detect the speaker’s or listener’s emotional state and may attempt to respond to it accordingly. When instead one of the interlocutors is a computer a number of questions arise, such as the following: To what extent are dialogue systems able to simulate such behaviors? Can we learn the mechanisms of emotional be- viors from observing and analyzing the behavior of human speakers? How can emotionsbeautomaticallyrecognizedfromauser’smimics,gesturesandspeech? What possibilities does a dialogue system have to express emotions itself? And, very importantly, would emotional system behavior be desirable at all? Given the state of ongoing research into incorporating emotions in dialogue systems we found it timely to organize a Tutorial and Research Workshop on A?ectiveDialogueSystems(ADS2004)atKlosterIrseein GermanyduringJune 14–16, 2004. After two successful ISCA Tutorial and Research Workshops on Multimodal Dialogue Systems at the same location in 1999 and 2002, we felt that a workshop focusing on the role of a?ect in dialogue would be a valuable continuation of the workshop series. Due to its interdisciplinary nature, the workshop attracted submissions from researchers with very di?erent backgrounds and from many di?erent research areas, working on, for example, dialogue processing, speech recognition, speech synthesis, embodied conversational agents, computer graphics, animation, user modelling, tutoring systems, cognitive systems, and human-computer inter- tion.
Author: Erik Marchi
Publisher: Springer Nature
ISBN: 981159323X
Category : Technology & Engineering
Languages : en
Pages : 453
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Book Description
This book compiles and presents a synopsis on current global research efforts to push forward the state of the art in dialogue technologies, including advances to language and context understanding, and dialogue management, as well as human–robot interaction, conversational agents, question answering and lifelong learning for dialogue systems.
Author: Emiel Krahmer
Publisher: Springer Science & Business Media
ISBN: 3642155723
Category : Computers
Languages : en
Pages : 363
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Book Description
Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field has evolved substantially. Perhaps the most important new development is the current emphasis on data-oriented methods and empirical evaluation. Progress in related areas such as machine translation, dialogue system design and automatic text summarization and the resulting awareness of the importance of language generation, the increasing availability of suitable corpora in recent years, and the organization of shared tasks for NLG, where different teams of researchers develop and evaluate their algorithms on a shared, held out data set have had a considerable impact on the field, and this book offers the first comprehensive overview of recent empirically oriented NLG research.
Author: Sandra Carberry
Publisher: MIT Press
ISBN: 9780262031677
Category : Computers
Languages : en
Pages : 316
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Book Description
Sandra Carberry addresses the problem of creating computational strategies that can improve user-computer communication by assimilating ongoing dialogue and reasoning on the acquired knowledge. In most current natural language systems each query is treated as an isolated request for information regardless of its context in dialogue. Sandra Carberry addresses the problem of creating computational strategies that can improve user-computer communication by assimilating ongoing dialogue and reasoning on the acquired knowledge. Plan Recognition in Natural Language Dialogue critically examines plan recognition - the inference of an agent's goals and how he or she intends to achieve them. It describes significant models of plan inference and presents in detail the author's own model, which infers new goals from user utterances and integrates them into the system's model of the user's plan, incrementally expanding and adding detail to its beliefs about what the information seeker wants to do. Carberry then outlines computational strategies for interpreting two kinds of problematic utterances: utterances that violate the pragmatic rules of the system's world model and intersentential elliptical fragments. She also suggests directions for future research. Plan Recognition in Natural Language Dialogue is included in the ACL-MIT Press Series in Natural Language Processing edited by Aravind Joshi.
