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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… Altro …
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… Altro …
2012
ISBN: 1461445922
2013 Gebundene Ausgabe Bildbearbeitung, Bildverarbeitung, Grafik (EDV) / Bildverarbeitung, Data Mining (EDV), Elektronik, Data Mining, Digitale Signalverarbeitung (DSP), Mensch-Computer… Altro …
2012, ISBN: 9781461445920
2013 Buchschnitt verkürzt - gepflegter, sauberer Zustand - Ausgabejahr 2013 22552778/12 Versandkostenfreie Lieferung Adaptive Spoken Dialogue Systems,SRI,Wolfgang Minker,Platform Developm… Altro …
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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.
Informazioni dettagliate del libro - Towards Adaptive Spoken Dialog Systems by Alexander Schmitt Hardcover | Indigo Chapters
EAN (ISBN-13): 9781461445920
ISBN (ISBN-10): 1461445922
Copertina rigida
Copertina flessibile
Anno di pubblicazione: 2012
Editore: Alexander Schmitt
251 Pagine
Peso: 0,577 kg
Lingua: Englisch
Libro nella banca dati dal 2009-09-05T01:11:26+02:00 (Rome)
Pagina di dettaglio ultima modifica in 2024-03-23T14:53:23+01:00 (Rome)
ISBN/EAN: 1461445922
ISBN - Stili di scrittura alternativi:
1-4614-4592-2, 978-1-4614-4592-0
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : alexander wolf, mink, maria schmitt, wolfgang will, minke, wolfgang bücher
Titolo del libro: dialog, spoke, system, alexander wolfgang, schmitt buch
Dati dell'editore
Autore: Alexander Schmitt; Wolfgang Minker
Titolo: Towards Adaptive Spoken Dialog Systems
Editore: Springer; Springer US
254 Pagine
Anno di pubblicazione: 2012-09-19
New York; NY; US
Stampato / Fatto in
Peso: 5,266 kg
Lingua: Inglese
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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