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Towards Adaptive Spoken Dialog Systems - Alexander Schmitt, Wolfgang Minker
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Towards Adaptive Spoken Dialog Systems - Alexander Schmitt#Wolfgang Minker
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ISBN: 9781461445920

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This extensive study of new statistical approaches that allow recognition of negative dialog patterns in SDS fosters a flexible, portable and accurate approach to the topic, using methods based on acoustic, linguistic, and contextual features in spoken dialog. 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. Bücher / Fremdsprachige Bücher / Englische Bücher 978-1-4614-4592-0, Springer

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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 extensive study of new statistical approaches that allow recognition of negative dialog patterns in SDS fosters a flexible, portable and accurate approach to the topic, using methods based on acoustic, linguistic, and contextual features in spoken dialog. Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, Springer

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[ED: Buch], [PU: Springer-Verlag GmbH], Neuware - 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 monographexamines 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., [SC: 0.00], Neuware, gewerbliches Angebot, 244x127x22 mm, [GW: 577g]

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Towards Adaptive Spoken Dialog Systems - Minker, Wolfgang; Schmitt, Alexander
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ISBN: 9781461445920

ID: 994367

Presents techniques and tools to render SDS intelligent and answers on how to make next-generation's SDS adaptive, user-friendly and emotion-aware Applies novel research methods about emotion recognition and problem spotting on commercial SDS Describes how users perceive interactions with an SDS and identifies ways to automatically estimate user satisfaction at arbitrary points in a spoken human-machine interaction Technology Technology eBook, Springer New York

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Towards Adaptive Spoken Dialog Systems
Autor:

Alexander Schmitt

Titel:

Towards Adaptive Spoken Dialog Systems

ISBN-Nummer:

9781461445920

Detailangaben zum Buch - Towards Adaptive Spoken Dialog Systems


EAN (ISBN-13): 9781461445920
ISBN (ISBN-10): 1461445922
Gebundene Ausgabe
Erscheinungsjahr: 2012
Herausgeber: Springer-Verlag GmbH
251 Seiten
Gewicht: 0,577 kg
Sprache: Englisch

Buch in der Datenbank seit 05.09.2009 01:11:26
Buch zuletzt gefunden am 09.11.2016 13:54:45
ISBN/EAN: 9781461445920

ISBN - alternative Schreibweisen:
1-4614-4592-2, 978-1-4614-4592-0

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