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2012, ISBN: 1461445922
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2012, ISBN: 1461445922
[EAN: 9781461445920], Neubuch, [SC: 0.0], [PU: Springer New York], BILDBEARBEITUNG; BILDVERARBEITUNG; GRAFIK (EDV) / DATA MINING (EDV); ADAPTIVESPOKENDIALOGUESYSTEMS; DIALOGUESYSTEMS; EMO… Mehr…
ISBN: 9781461445920
In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Sp… Mehr…
2012
ISBN: 1461445922
2013 Gebundene Ausgabe Bildbearbeitung, Bildverarbeitung, Grafik (EDV) / Bildverarbeitung, Data Mining (EDV), Elektronik, Data Mining, Digitale Signalverarbeitung (DSP), Mensch-Computer… Mehr…
2012, ISBN: 9781461445920
2013 Buchschnitt verkürzt - gepflegter, sauberer Zustand - Ausgabejahr 2013 22552778/12 Versandkostenfreie Lieferung Adaptive Spoken Dialogue Systems,SRI,Wolfgang Minker,Platform Developm… Mehr…
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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.
Detailangaben zum Buch - Towards Adaptive Spoken Dialog Systems by Alexander Schmitt Hardcover | Indigo Chapters
EAN (ISBN-13): 9781461445920
ISBN (ISBN-10): 1461445922
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2012
Herausgeber: Alexander Schmitt
251 Seiten
Gewicht: 0,577 kg
Sprache: Englisch
Buch in der Datenbank seit 2009-09-05T01:11:26+02:00 (Berlin)
Detailseite zuletzt geändert am 2024-03-23T14:53:23+01:00 (Berlin)
ISBN/EAN: 1461445922
ISBN - alternative Schreibweisen:
1-4614-4592-2, 978-1-4614-4592-0
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: alexander wolf, mink, maria schmitt, wolfgang will, minke, wolfgang bücher
Titel des Buches: dialog, spoke, system, alexander wolfgang, schmitt buch
Daten vom Verlag:
Autor/in: Alexander Schmitt; Wolfgang Minker
Titel: Towards Adaptive Spoken Dialog Systems
Verlag: Springer; Springer US
254 Seiten
Erscheinungsjahr: 2012-09-19
New York; NY; US
Gedruckt / Hergestellt in Niederlande.
Gewicht: 5,266 kg
Sprache: Englisch
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XIV, 254 p.
BB; Signal, Image and Speech Processing; Hardcover, Softcover / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Elektronik; Verstehen; Adaptive Spoken Dialogue Systems; Dialogue Systems; Emotion Recognition; Interaction Modeling; Linguistic Modeling; Machine Learning; Paralinguistic Modeling; Platform Development; SRI; Wolfgang Minker; Data Mining and Knowledge Discovery; User Interfaces and Human Computer Interaction; Computer Imaging, Vision, Pattern Recognition and Graphics; Signal, Speech and Image Processing; Data Mining and Knowledge Discovery; User Interfaces and Human Computer Interaction; Computer Imaging, Vision, Pattern Recognition and Graphics; Digitale Signalverarbeitung (DSP); Data Mining; Wissensbasierte Systeme, Expertensysteme; Mensch-Computer-Interaktion; Bildverarbeitung; BC; EA
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.
Monitoring Adaptive Spoken Dialog SystemsIntroduction.- Background and Related Research.- Interaction Modeling and Platform Development.- Novel Strategies for Emotion Recognition.- Novel Approaches to Pattern-based Interaction Quality Modeling.- Statistically Modeling and Predicting Task Success.- Conclusion and Future Directions.
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.
Monitoring Adaptive Spoken Dialog SystemsPresents 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
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