Laughter is an universal social sign that plays a key role in human communication and interactions. It strengthens the bonds among people and provides a positive feedback to the interlocutor during a conversation. Given the relevance of laughter for humans’ well-being, a system able to automatically recognize laughter episodes would have several applications. Most of the existing datasets containing laughter episodes  only report video and audio information. However, it has been studied that laughter is also characterized by movements and physiological reactions. The cues which characterize laughter episodes might however be confounded with tasks which elicit similar reactions such as cognitive load and intense movements such as clapping hands. To investigate the possibility of recognizing laughter episodes using physiological and movement data we have created the USI_Laughs dataset. USI_Laughs dataset The USI_Laughs dataset contains laughter episodes from 34 participants (28 males and 6 females) of age between 22 and 37 (Mean = 26.70, SD = … Read More

ECO dataset

The ECO (Electricity Consumption & Occupancy) data set is a comprehensive data set for non-intrusive load monitoring and occupancy detection research. It was collected in 6 Swiss households over a period of 8 months. For each of the households, the ECO data set provides 1 Hz aggregate consumption data. Each measurement contains data on current, voltage, and phase shift for each of the three phases in the household. 1 Hz plug-level data measured from selected appliances. Occupancy information measured through a tablet computer (manual labeling) and a passive infrared sensor (in some of the households). We make the ECO data set available to the research community. The data set may be obtained from or via its own DOI, but we always like to receive a short description of what you plan to do with the data via e-mail to Wilhelm Kleiminger. Further information about the dataset is available in