Multicriteria Neural Network Design in the Speech-based Emotion Recognition Problem

Christina Brester, Eugene Semenkin, Maxim Sidorov, Olga Semenkina

Abstract

In this paper we introduce the two-criterion optimization model to design multilayer perceptrons taking into account two objectives, which are the classification accuracy and computational complexity. Using this technique, it is possible to simplify the structure of neural network classifiers and at the same time to keep high classification accuracy. The main benefits of the approach proposed are related to the automatic choice of activation functions, the possibility of generating the ensemble of classifiers, and the embedded feature selection procedure. The cooperative multi-objective genetic algorithm is used as an optimizer to determine the Pareto set approximation in the two-criterion problem. The effectiveness of this approach is investigated on the speech-based emotion recognition problem. According to the results obtained, the usage of the proposed technique might lead to the generation of classifiers comprised by fewer neurons in the input and hidden layers, in contrast to conventional models, and to an increase in the emotion recognition accuracy by up to a 4.25% relative improvement due to the application of the ensemble of classifiers.

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Paper Citation


in Harvard Style

Brester C., Semenkin E., Sidorov M. and Semenkina O. (2015). Multicriteria Neural Network Design in the Speech-based Emotion Recognition Problem . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 621-628. DOI: 10.5220/0005571806210628


in Bibtex Style

@conference{icinco15,
author={Christina Brester and Eugene Semenkin and Maxim Sidorov and Olga Semenkina},
title={Multicriteria Neural Network Design in the Speech-based Emotion Recognition Problem},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={621-628},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005571806210628},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Multicriteria Neural Network Design in the Speech-based Emotion Recognition Problem
SN - 978-989-758-122-9
AU - Brester C.
AU - Semenkin E.
AU - Sidorov M.
AU - Semenkina O.
PY - 2015
SP - 621
EP - 628
DO - 10.5220/0005571806210628