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Emotion Recognition from Speech using Representation Learning in Extreme Learning Machines

Topics: Applications: Image Processing and Artificial Vision, Pattern Recognition, Decision Making, Industrial and Real World applications, Financial Applications, Neural Prostheses and Medical Applications, Neural based Data Mining and Complex Information Processing, Neural Network Software and Applications, Applications of Deep Neural networks, Robotics and Control Applications; Deep Learning; Learning Paradigms and Algorithms

Authors: Stefan Glüge 1 ; Ronald Böck 2 and Thomas Ott 1

Affiliations: 1 Zurich University of Applied Sciences, Switzerland ; 2 Otto-von-Guericke University, Germany

ISBN: 978-989-758-274-5

Keyword(s): Emotion Recognition from Speech, Representation Learning, Extreme Learning Machine.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Learning Paradigms and Algorithms ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: We propose the use of an Extreme Learning Machine initialised as auto-encoder for emotion recognition from speech. This method is evaluated on three different speech corpora, namely EMO-DB, eNTERFACE and SmartKom. We compare our approach against state-of-the-art recognition rates achieved by Support Vector Machines (SVMs) and a deep learning approach based on Generalised Discriminant Analysis (GerDA). We could improve the recognition rate compared to SVMs by 3%-14% on all three corpora and those compared to GerDA by 8%-13% on two of the three corpora.

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Paper citation in several formats:
Glüge S., Böck R. and Ott T. (2017). Emotion Recognition from Speech using Representation Learning in Extreme Learning Machines.In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-274-5, pages 179-185. DOI: 10.5220/0006485401790185

@conference{ijcci17,
author={Stefan Glüge and Ronald Böck and Thomas Ott},
title={Emotion Recognition from Speech using Representation Learning in Extreme Learning Machines},
booktitle={Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2017},
pages={179-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006485401790185},
isbn={978-989-758-274-5},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Emotion Recognition from Speech using Representation Learning in Extreme Learning Machines
SN - 978-989-758-274-5
AU - Glüge S.
AU - Böck R.
AU - Ott T.
PY - 2017
SP - 179
EP - 185
DO - 10.5220/0006485401790185

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