Correction: Automatic detection of expressed emotion from five-minute speech samples: Challenges and opportunities

Authors

Helen L. Fisher (ORCID: https://orcid.org/0000-0003-4174-2126)
André Bittar (ORCID: https://orcid.org/0000-0001-6587-0080)
Johnny Downs (ORCID: https://orcid.org/0000-0002-8061-295X)
Heidi Christensen (ORCID: https://orcid.org/0000-0003-3028-5062)
Nicholas Cummins (ORCID: https://orcid.org/0000-0002-1178-917X)
Bahman Mirheidari (ORCID: https://orcid.org/0009-0009-8679-203X)

Publication Details

Journal: PLoS ONE
Published: 2025-12-04
DOI: https://doi.org/10.1371/journal.pone.0338220
Primary Topic: Emotion and Mood Recognition
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Institute for Health and Care Research
Department of Health and Social Care
King's College London
NIHR Maudsley Biomedical Research Centre
Medical Research Council
Economic and Social Research Council

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article

Correction: Automatic detection of expressed emotion from five-minute speech samples: Challenges and opportunities

Helen L. Fisher, André Bittar, Johnny Downs, Heidi Christensen et al.

Dec 4, 2025

PLoS ONE

Emotion and Mood Recognition

article

Correction: Automatic detection of expressed emotion from five-minute speech samples: Challenges and opportunities

Helen L. Fisher, André Bittar, Johnny Downs, Heidi Christensen, Nicholas Cummins, Bahman Mirheidari

December 4, 2025article en

Abstract

No abstract available for this paper.

PLoS ONEVol. 20(12)

National Institute for Health and Care Research, Department of Health and Social Care, King's College London, NIHR Maudsley Biomedical Research Centre, Medical Research Council, Economic and Social Research Council

Openalex Percentile: Top 59%

Emotion and Mood Recognition

DOI Open Access PDF OpenAlex

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