Towards Adaptive Spoken Dialog Systems

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Synopsis

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.

Book details

Edition:
2013
Author:
Alexander Schmitt, Wolfgang Minker
ISBN:
9781461445937
Related ISBNs:
9781461445920
Publisher:
Springer New York
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2020-12-31
Usage restrictions:
Copyright
Copyright date:
2013
Copyright by:
Springer New York, New York, NY 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Nonfiction, Technology