Towards Adaptive Spoken Dialog Systems Book

In Monitoring Adaptive Spoken Dialog Systems authors Alexander Schmitt and Wolfgang Minker extensively study novel statistical approaches that allow for recognition of negative dialog patterns in SDS. The presented statistical procedures allow a flexible, portable and accurate use. Starting with the foundations of machine learning and pattern recognition, this text also investigate 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 of real users. Further, 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 inspiration for future research and development - not only for spoken dialog systems but for data-driven approaches to human-machine interaction in general.Read More