Evidence map›Paper›PMID 40109557›Full record

ArticleLanguage resources and evaluation2025

The Reading Everyday Emotion Database (REED): a set of audio-visual recordings of emotions in music and language.

Jia Hoong Ong, Florence Yik Nam Leung, Fang Liu

Abstract read
In one paragraph

Article in Language resources and evaluation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jia Hoong OngSchool of Psychology and Clinical Language Sciences, University of Reading, Harry Pitt Building, Earley Gate, Reading, RG6 6AL UK.ORCID 0000-0003-1503-8311
Florence Yik Nam LeungSchool of Psychology and Clinical Language Sciences, University of Reading, Harry Pitt Building, Earley Gate, Reading, RG6 6AL UK.ORCID 0000-0001-9136-1263
Fang LiuSchool of Psychology and Clinical Language Sciences, University of Reading, Harry Pitt Building, Earley Gate, Reading, RG6 6AL UK.ORCID 0000-0002-7776-0222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most audio-visual (AV) emotion databases consist of clips that do not reflect real-life emotion processing (e.g., professional actors in bright studio-like environment), contain only spoken clips, and none have sung clips that express complex emotions. Here, we introduce a new AV database, the Reading Everyday Emotion Database (REED), which directly addresses those gaps. We recorded the faces of everyday adults with a diverse range of acting experience expressing 13 emotions-neutral, the six basic emotions (angry, disgusted, fearful, happy, sad, surprised), and six complex emotions (embarrassed, hopeful, jealous, proud, sarcastic, stressed)-in two auditory domains (spoken and sung) using everyday recording devices (e.g., laptops, mobile phones, etc.). The recordings were validated by an independent group of raters. We found that: intensity ratings of the recordings were positively associated with recognition accuracy; and the basic emotions, as well as the Neutral and Sarcastic emotions, were recognised more accurately than the other complex emotions. Emotion recognition accuracy also differed by utterance. Exploratory analysis revealed that recordings of those with drama experience were better recognised than those without. Overall, this database will benefit those who need AV clips with natural variations in both emotion expressions and recording environment. Supplementary Information: The online version contains supplementary material available at 10.1007/s10579-023-09698-5.

Indexed as

Audio-visualDatabaseEmotionSongSpeechStimulus set

Identifiers

PMID40109557
PMCPMC11913894

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.