Description |
created by trained speakers reading the same text with different emotions |
made by asking people or actors to read a scenario containing various emotions |
extracted from TV shows, YouTube videos, call centers, etc. |
Natural emotions |
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Contains contextual information |
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Contains situational information |
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Discrete and separable emotions |
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Single emotions at a time |
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Widely used |
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Standardized |
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Easy to model |
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Inter corpora results are comparable |
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Large Number of emotions |
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Used in real-world emotion systems modeling |
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Controlled privacy and copyright |
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Examples |
EMO-DB [55]
DES [56]
RAVDESS [57]
TESS [58]
CREMA-D [59]
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IEMOCAP [60]
Belfast [61]
NIMITEK [62]
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