Table 1 Comparison of the K-EmoCon dataset with the existing multimodal emotion recognition datasets.
Name (year) | Size | Modalities | Spon. vs. posed | Natural vs. induced | Annotation method | Annotation type | Context |
|---|---|---|---|---|---|---|---|
IEMOCAP (2008)51 | 10 | Videos, face motion capture, gesture, speech (audio & transcribed) | Both | Both†| Per dialog turn | S, E | Dyadic |
SEMAINE (2011)52 | 150 | Videos, FAUs, speech (audio & transcribed) | Spon. | Induced | Trace-style continuous | E | Dyadic |
MAHNOB-HCI (2011)23 | 27 | Videos (face and body), eye gaze, audio, biosignals (EEG, GSR, ECG, respiration, skin temp.) | Spon. | Induced | Per stimuli | S | Individual |
DEAP (2012)24 | 32 | Face videos, biosignals (EEG, GSR, BVP, respiration, skin temp., EMG & EOG) | Spon. | Induced | Per stimuli | S | Individual |
DECAF (2015)25 | 30 | NIR face videos, biosignals (MEG, hEOG, ECG, tEMG) | Spon. | Induced | Per stimuli | S | Individual |
ASCERTAIN (2016)26 | 58 | Facial motion units (EMO), biosignals (ECG, GSR, EEG) | Spon. | Induced | Per stimuli | S | Individual |
MSP-IMPROV (2016)53 | 12 | Face videos, speech audio | Both | Both†| Per dialog turn | E | Dyadic |
DREAMER (2017)27 | 23 | Biosignals (EEG, ECG) | Spon. | Induced | Per stimuli | S | Individual |
AMIGOS (2018)28 | 40 | Vidoes (face & body), biosignals (EEG, ECG, GSR) | Spon. | Induced | Per stimuli | S, E | Individual, Group |
MELD (2019)38 | 7 | Videos, speech (audio & transcribed) | Both | Both†| Turn-based | E | Dyadic, Group |
CASE (2019)29 | 30 | Biosignals (ECG, respiration, BVP, GSR, skin temp., EMG) | Spon. | Induced | Trace-style continuous | S | Individual |
CLAS (2020)100 | 64 | Biosignals (ECG, PPG, EDA), accelerometer | Spon. | Induced | Per stimuli/task | Predefined‡ | Individual |
K-EmoCon (2020) | 32 | Videos (face, gesture), speech audio, accelerometer, biosignals (EEG, ECG, BVP, EDA, skin temp.) | Spon. | Natural | Interval-based continuous | S, P, E | Dyadic |