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  • © 2013

Towards 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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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiv
  2. Introduction

    • Alexander Schmitt, Wolfgang Minker
    Pages 1-16
  3. Background and Related Research

    • Alexander Schmitt, Wolfgang Minker
    Pages 17-61
  4. Interaction Modeling and Platform Development

    • Alexander Schmitt, Wolfgang Minker
    Pages 63-97
  5. Novel Strategies for Emotion Recognition

    • Alexander Schmitt, Wolfgang Minker
    Pages 99-152
  6. Novel Approaches to Pattern-based Interaction Quality Modeling

    • Alexander Schmitt, Wolfgang Minker
    Pages 153-184
  7. Statistically Modeling and Predicting Task Success

    • Alexander Schmitt, Wolfgang Minker
    Pages 185-203
  8. Conclusion and Future Directions

    • Alexander Schmitt, Wolfgang Minker
    Pages 205-218
  9. Back Matter

    Pages 219-251

About this book

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.

Authors and Affiliations

  • Institute of Communications Engineering, University of Ulm, Ulm, Germany

    Alexander Schmitt

  • University of Ulm, Institute of Communications Engineering, Ulm, Germany

    Wolfgang Minker

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access