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Emotion Classification from Speech by an Ensemble Strategy

Authors:

Pedro J.S. Cardoso,

João M.F. RodriguesAuthors Info & Claims

DSAI '22: Proceedings of the 10th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

Pages 85 - 90

https://doi.org/10.1145/3563137.3563170

Published: 25 May 2023 Publication History

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Abstract

Humans are prepared to comprehend each other's emotions through subtle body movements and speech expressions, and from those, they change the way they deliver/understand messages when communicating between them. Socially assistive robots need to empower their ability in recognizing emotions in a way to change the interaction with humans, especially with elders. This paper presents a framework for speech emotion prediction supported by an ensemble of distinct out-of-the-box methods, being the main contribution of the integration of the outputs of those methods in a single prediction consistent with the expression presented by the system's user. Results show a classification accuracy of 75.56% over the RAVDESS dataset and 86.43% in a group of datasets constituted by RAVDESS, SAVEE, and TESS.

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Cited By

Cardoso PRodrigues JNovais R(2023)Multimodal Emotion Classification Supported in the Aggregation of Pre-trained Classification ModelsComputational Science – ICCS 202310.1007/978-3-031-36030-5_35(433-447)Online publication date: 26-Jun-2023
https://doi.org/10.1007/978-3-031-36030-5_35
Rodrigues JCardoso P(2023)Body-Focused Expression Analysis: A Conceptual FrameworkUniversal Access in Human-Computer Interaction10.1007/978-3-031-35897-5_42(596-608)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35897-5_42

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cover image ACM Other conferences

DSAI '22: Proceedings of the 10th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

August 2022

237 pages

ISBN:9781450398077

DOI:10.1145/3563137

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 May 2023

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Research-article
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Portuguese Foundation for Science and Technology (FCT), project LARSyS - FCT Project

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DSAI 2022

DSAI 2022: 10th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion

August 31 - September 2, 2022

Lisbon, Portugal

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Overall Acceptance Rate 17 of 23 submissions, 74%

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Cited By

Cardoso PRodrigues JNovais R(2023)Multimodal Emotion Classification Supported in the Aggregation of Pre-trained Classification ModelsComputational Science – ICCS 202310.1007/978-3-031-36030-5_35(433-447)Online publication date: 26-Jun-2023
https://doi.org/10.1007/978-3-031-36030-5_35
Rodrigues JCardoso P(2023)Body-Focused Expression Analysis: A Conceptual FrameworkUniversal Access in Human-Computer Interaction10.1007/978-3-031-35897-5_42(596-608)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35897-5_42

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