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Recurrent Neural Network Interaction Quality Estimation

  • Louisa PragstEmail author
  • Stefan Ultes
  • Wolfgang Minker
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 427)

Abstract

Getting a good estimation of the Interaction Quality (IQ) of a spoken dialogue helps to increase the user satisfaction as the dialogue strategy may be adapted accordingly. Therefore, some research has already been conducted in order to automatically estimate the Interaction Quality. This article adds to this by describing how Recurrent Neural Networks may be used to estimate the Interaction Quality for each dialogue turn and by evaluating their performance on this task. Here, we will show that RNNs may outperform non-recurrent neural networks.

Keywords

RNN Sequential data Quality of dialogue Recurrent neural network Neural network Interaction quality User satisfaction Spoken dialogue system 

Notes

Acknowledgements

This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 645012.

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Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  1. 1.Institute of Communications EngineeringUlm UniversityUlmGermany
  2. 2.Engineering DepartmentCambridge UniversityCambridgeUK

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