Proceedings Of The Paralinguistic Information And Its Integration In Spoken Dialogue Systems Workshop
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Proceedings of the Paralinguistic Information and its Integration in Spoken Dialogue Systems Workshop
Author: Ramón López-Cózar Delgado
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-08-27
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.
Towards Adaptive Spoken Dialog Systems
Author: Alexander Schmitt
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-09-19
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.
Natural Language Dialog Systems and Intelligent Assistants
This book covers state-of-the-art topics on the practical implementation of Spoken Dialog Systems and intelligent assistants in everyday applications. It presents scientific achievements in language processing that result in the development of successful applications and addresses general issues regarding the advances in Spoken Dialog Systems with applications in robotics, knowledge access and communication. Emphasis is placed on the following topics: speaker/language recognition, user modeling / simulation, evaluation of dialog system, multi-modality / emotion recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and healthcare applications.