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Unrequited Emotions: Investigating the Gaps in Motivation and Practice in Speech Emotion Recognition Research

Proceedings of Computational Affective Science (CAS) @ LREC 2026

DOI:10.63317/42e4sre4izeu

Abstract

Critical analyses of emotion recognition technology have raised ethical concerns around task validity and potential downstream impacts, urging researchers to ensure alignment between their stated motivations and practice. However, these discussions have not adequately influenced or drawn from research on speech emotion recognition (SER). We address this gap by conducting a systematic survey of SER research to uncover what stated motivations drive this work and if they align with the datasets and emotions studied. We find that while SER research identifies appealing goals—such as well-situated voice-activated systems or healthcare applications—commonly-used datasets do not reflect these proposed deployment contexts, thus presenting a gap between motivations and research practices. We argue that such gaps engender ethical concerns, and that SER research should reassert itself with concrete use-cases to prevent misinterpretations, misuse, and downstream harms.

Details

Paper ID
lrec2026-ws-cas-06
Pages
pp. 57-73
BibKey
wong-etal-2026-unrequited
Editors
Christopher Bagdon, Krishnapriya Vishnubhotla, Kristen A. Lindquist, Lyle Ungar, Roman Klinger, Saif M. Mohammad
Publisher
European Language Resources Association (ELRA)
ISSN
N/A
ISBN
N/A
Workshop
Proceedings of Computational Affective Science (CAS) @ LREC 2026
Location
Palma, Mallorca, Spain
Date
11 - 16 May 2026

Authors

  • TW

    Taryn Wong

  • ZT

    Zeerak Talat

  • HA

    Hanan Aldarmaki

  • AF

    Anjalie Field

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