SER Datasets

Speech Emotion Recognition (SER) Datasets: A collection of datasets (count=77) for the purpose of emotion recognition/detection in speech. The table is chronologically ordered and includes a description of the content of each dataset along with the emotions included. The table can be browsed, sorted and searched under https://superkogito.github.io/SER-datasets/ | Dataset | Year | Content | Emotions | Format | Size | Language | Paper | Access | License | |:--------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------|:---------------------|:------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------| | _nEmo | ₂₀₂₄ | _{3 hours of samples recorded with the participation of nine actors.} | _{6 emotions: anger, fear, happiness, sadness, surprised, and neutral.} | _Audio | _{0.434 GB} | _Polish | _{nEMO: Dataset of Emotional Speech in Polish} | _Open | _{CC BY 4.0} | | _MDER | ₂₀₂₄ | _{2000 voice records of people speaking Moroccan dialect.} | _{5 emotions: Neutral, Happy, Sad, Angry and Fearful.} | _Audio | _{0.187 GB} | _{Arabic Moroccan} | _-- | _Open | _{CC BY 4.0} | | _EMOVOME | ₂₀₂₄ | _{999 spontaneous voice messages from 100 Spanish speakers, collected from real conversations on a messaging app.} | _{Valence & arrousal dimensions and 7 emotions: happiness, disgust, anger, surprise, fear, sadness, and neutral.} | _Audio | _-- | _Spanish | _{EMOVOME Database: Advancing Emotion Recognition in Speech Beyond Staged Scenarios} | _{Partially open} | _{CC BY 4.0} | | _EMNS | ₂₀₂₃ | _{1206 high quality labeled utterances by one female speaker (2-3 hours).} | _{Anger, excitement, disgust, happiness, surprise, sadness, and neutral (plus sarcasm)} | _Audio | _{0.042 GB} | _{English (British)} | _{EMNS /Imz/ Corpus: An emotive single-speaker dataset for narrative storytelling in games, television and graphic novels} | _Open | _{Apache 2.0} | | _CAVES | ₂₀₂₃ | _{Full hd visual recordings of 10 native cantonese speakers uttering 50 sentences.} | _{Anger, happiness, sadness, surprise, fear, disgust and neutral} | _Audio | _{47 GB} | _{Chinese (cantonese)} | _{A Cantonese Audio-Visual Emotional Speech (CAVES) dataset} | _Open | _{Available for research purposes only} | | _BANSpEmo