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Automatic Speech Recognition Based on Neural Networks Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Stress, Arousal, and Stress Detector Trained on Acted Speech Database

Authors : Róbert Sabo, Milan Rusko, Andrej Ridzik, Jakub Rajčáni

Published in: Speech and Computer

Publisher: Springer International Publishing

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Abstract

This paper reports on initial experiments with the creation of a suitable database for training and testing systems for stress detection in speech and first experimental results. Based on the psychological understanding of the concepts of stress and emotion, we operationalized stress as a level of arousal, which can be detected in speech. We describe here a speech database with three levels of “acted stress” and three levels of soothing. For the very first experiment performed on the database we detect different levels of stress using Gaussian mixture models. The accuracy of detecting three levels of stress was 89 % for speakers included in the training database and 73 % for speakers whose recordings were not used during the adaptation of the GMM models.

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previous chapter Statistical Analysis of Acoustical Parameters in the Voice of Children with Juvenile Dysphonia
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Metadata
Title
Stress, Arousal, and Stress Detector Trained on Acted Speech Database
Authors
Róbert Sabo
Milan Rusko
Andrej Ridzik
Jakub Rajčáni
Copyright Year
2016
Book
Speech and Computer

Print ISBN: 978-3-319-43957-0

Electronic ISBN: 978-3-319-43958-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-43958-7_82

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