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Effective Speech Features for Cognitive Load Assessment: Classification and Regression

English · Paperback / Softback

Description

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This thesis is about the effectiveness of speech features for cognitive load assessment, with particular attention being paid to new perspectives of this research area. A new cognitive load database, called CoLoSS, is introduced containing speech recordings of users who performed a learning task. Various acoustic features from different categories including prosody, voice quality, and spectrum are investigated in terms of their relevance. Moreover, Teager energy parameters, which have proven highly successful in stress detection, are introduced for cognitive load assessment and it is demonstrated how automatic speech recognition technology can be used to extract potential indicators.The suitability of the extracted features is systematically evaluated by recognition experiments with speaker-independent systems designed for discriminating between three levels of load. Additionally, a novel approach to speech-based cognitive load modelling is introduced, whereby the load is represented as a continuous quantity and its prediction can thus be regarded as a regression problem.

Product details

Authors Robert Herms
Publisher Universitätsverlag Chemnitz
 
Languages English
Product format Paperback / Softback
Released 01.01.2019
 
EAN 9783961000876
ISBN 978-3-96100-087-6
Series Wissenschaftliche Schriftenreihe Dissertationen der Medieninformatik
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT

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