Abstract

The RAVDESS is a validated multimodal database of emotional speech and song. The database is gender balanced consisting of 24 professional actors, vocalizing lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity, with an additional neutral expression. All conditions are available in face-and-voice, face-only, and voice-only formats. The set of 7356 recordings were each rated 10 times on emotional validity, intensity, and genuineness. Ratings were provided by 247 individuals who were characteristic of untrained research participants from North America. A further set of 72 participants provided test-retest data. High levels of emotional validity and test-retest intrarater reliability were reported. Corrected accuracy and composite "goodness" measures are presented to assist researchers in the selection of stimuli. All recordings are made freely available under a Creative Commons license and can be downloaded at https://doi.org/10.5281/zenodo.1188976.

Keywords

DisgustSurpriseFacial expressionPsychologyEmotional expressionSet (abstract data type)AudiologyFace (sociological concept)Speech recognitionCognitive psychologyAngerComputer scienceLinguisticsCommunicationSocial psychologyMedicine

MeSH Terms

AdultDatabasesFactualEmotionsFacial ExpressionFemaleHumansLanguageMaleMusicNorth AmericaSpeechVideo RecordingVoiceYoung Adult

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Publication Info

Year
2018
Type
article
Volume
13
Issue
5
Pages
e0196391-e0196391
Citations
1609
Access
Closed

Citation Metrics

1609
OpenAlex
228
Influential
1342
CrossRef

Cite This

Steven R. Livingstone, Frank Russo (2018). The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. PLoS ONE , 13 (5) , e0196391-e0196391. https://doi.org/10.1371/journal.pone.0196391

Identifiers

DOI
10.1371/journal.pone.0196391
PMID
29768426
PMCID
PMC5955500

Data Quality

Data completeness: 90%