UC3M4Safety Database - WEMAC: Emotional labelling
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detection of these situations and study how to react in a comprehensive, coordinated and effective way to protect them in the most optimal way possible.The emotional labelling file contains the labels reported by the participants (no Gender-based Violence Victims) after watching each clip of one of the two sets of 14 videos' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Affective computing","Audiovisual stimuli","Basic emotions","Gender-based violence","Gender perspective","Machine Learning"]} <|eot_id|>
 Here is the Description of a dataset. Description:'EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detection of these situations and study how to react in a comprehensive, coordinated and effective way to protect them in the most optimal way possible.The emotional labelling file contains the labels reported by the participants (no Gender-based Violence Victims) after watching each clip of one of the two sets of 14 videos' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detection of these situations and study how to react in a comprehensive, coordinated and effective way to protect them in the most optimal way possible.The emotional labelling file contains the labels reported by the participants (no Gender-based Violence Victims) after watching each clip of one of the two sets of 14 videos
Affective computing; Audiovisual stimuli; Basic emotions; Gender-based violence; Gender perspective; Machine Learning