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Towards Adaptive Spoken Dialog Systems - nuovo libro

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Towards Adaptive Spoken Dialog Systems - nuovo libro

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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 Sp… Altro …

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Towards Adaptive Spoken Dialog Systems - Wolfgang Minker; Alexander Schmitt
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Informazioni dettagliate del libro - Towards Adaptive Spoken Dialog Systems


EAN (ISBN-13): 9781461445937
ISBN (ISBN-10): 1461445930
Anno di pubblicazione: 2012
Editore: Springer New York
251 Pagine
Lingua: eng/Englisch

Libro nella banca dati dal 2012-08-09T00:01:44+02:00 (Zurich)
Pagina di dettaglio ultima modifica in 2024-03-23T14:53:23+01:00 (Zurich)
ISBN/EAN: 9781461445937

ISBN - Stili di scrittura alternativi:
1-4614-4593-0, 978-1-4614-4593-7
Stili di scrittura alternativi e concetti di ricerca simili:
Autore del libro : wolfgang schmit, alexander wolf, mink, schmitt, minke
Titolo del libro: dialog, spoke, system, alexander wolfgang


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
Lingua: Inglese
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XIV, 254 p.

EA; E107; eBook; Nonbooks, PBS / 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; B; Signal, Image and Speech Processing; 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; Engineering; Digitale Signalverarbeitung (DSP); Data Mining; Wissensbasierte Systeme, Expertensysteme; Mensch-Computer-Interaktion; Bildverarbeitung; BB

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 Systems

Introduction.- 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 Systems

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



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