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Authors: Marco Nicolini and Stavros Ntalampiras

Affiliation: LIM – Music Informatics Laboratory Department of Computer Science University of Milan, Italy

Keyword(s): Audio Pattern Recognition, Machine Learning, Transfer Learning, Convolutional Neural Network, YAMNet, Multilingual Speech Emotion Recognition.

Abstract: This article approaches the Speech Emotion Recognition (SER) problem with the focus placed on multilingual settings. The proposed solution consists in a hierarchical scheme the first level of which identifies the speaker’s gender and the second level predicts the speaker’s emotional state. We elaborate with three classifiers of increased complexity, i.e. k-NN, transfer learning based on YAMNet and Bidirectional Long Short-Term Memory neural networks. Importantly, model learning, validation and testing consider the full range of the big-six emotions, while the dataset has been assembled using well-known SER datasets representing six different languages. The obtained results show differences in classifying all data against only female or male data with respect to all classifiers. Interestingly, a-priori genre recognition can boost the overall classification performance.

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Paper citation in several formats:
Nicolini, M. and Ntalampiras, S. (2023). A Hierarchical Approach for Multilingual Speech Emotion Recognition. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-626-2; ISSN 2184-4313, SciTePress, pages 679-685. DOI: 10.5220/0011714800003411

@conference{icpram23,
author={Marco Nicolini. and Stavros Ntalampiras.},
title={A Hierarchical Approach for Multilingual Speech Emotion Recognition},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2023},
pages={679-685},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011714800003411},
isbn={978-989-758-626-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - A Hierarchical Approach for Multilingual Speech Emotion Recognition
SN - 978-989-758-626-2
IS - 2184-4313
AU - Nicolini, M.
AU - Ntalampiras, S.
PY - 2023
SP - 679
EP - 685
DO - 10.5220/0011714800003411
PB - SciTePress

- Science and Technology Publications, Lda.
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