Emotion Modelling via Speech Content and Prosody: In Computer Games and Elsewhere

Chapter
Part of the Socio-Affective Computing book series (SAC, volume 4)

Abstract

The chapter describes a typical modern speech emotion recognition engine as can be used to enhance computer games’ or other technical systems’ emotional intelligence. Acquisition of human affect via the spoken content and its prosody and further acoustic features is highlighted. Features for both of these information streams are shortly discussed along chunking of the stream. Decision making with and without training data is presented, each. A particular focus is then laid on autonomous learning and adaptation methods as well as the required calculation of confidence measures. Practical aspects include the encoding of the information, distribution of the processing, and available toolkits. Benchmark performances are given by typical competitive challenges in the field.

Keywords

Speech Signal Emotion Recognition Acoustic Feature Independent Component Analysis Automatic Speech Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The author acknowledges the support of the European Union’s Horizon 2020 Framework Programme under grant agreement no. 645378 (ARIA-VALUSPA).

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Imperial College LondonLondonUK

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