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Among the seventeen Sustainable Development Goals (SDGs) proposed within the2030 Agenda and adopted by all the United Nations member states, the Fifth SDGis a call for action to turn Gender Equality into a fundamental human right andan essential foundation for a better world. It includes the eradication of alltypes of violence against women. Within this context, the UC3M4Safety researchteam aims to develop Bindi. This is a cyber-physical system which includesembedded Artificial Intelligence algorithms, for user real-time monitoringtowards the detection of affective states, with the ultimate goal of achievingthe early detection of risk situations for women. On this basis, we make use ofwearable affective computing including smart sensors, data encryption forsecure and accurate collection of presumed crime evidence, as well as theremote connection to protecting agents. Towards the development of such system,the recordings of different laboratory and into-the-wild datasets are inprocess. These are contained within the UC3M4Safety Database. Thus, this paperpresents and details the first release of WEMAC, a novel multi-modal dataset,which comprises a laboratory-based experiment for 47 women volunteers that wereexposed to validated audio-visual stimuli to induce real emotions by using avirtual reality headset while physiological, speech signals and self-reportswere acquired and collected. We believe this dataset will serve and assistresearch on multi-modal affective computing using physiological and speechinformation.

WEMAC: Women and Emotion Multi-modal Affective Computing dataset