Simulating Deceptive Cues of Joy in Humanoid Robots

Endraß, Birgit; Haering, Markus; Akila, G.; André, Elisabeth

doi:10.1007/978-3-319-09767-1_20

Cited by 3 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…UGC image and video data will include a large proportion of emotion expression driven by communicative purposes and manifested according to learned cultural conventions (and varying in how closely it represents what the person is "really" feeling), but it is nonetheless a response to a naturally arising context [95,116]. For an AI system, it will be important to be able to interpret (and emulate [46]) both cues that can be consciously mediated (such as vocal pitch) and cues that (largely) cannot (such as pulse rate)-and to use the two different types of information appropriately in interaction. (Here, we set aside the effects of being recorded in the first place, which are nearly unminimizable for any kind of video data [38].)…”

Section: Interaction Training For Ai Systemsmentioning

confidence: 99%

Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Version)

Krell¹,

Bernd²,

Li³

et al. 2017

Preprint

View full text Add to dashboard Cite

Social multimedia users are increasingly sharing all kinds of data about the world. They do this for their own reasons, not to provide data for field studies-but the trend presents a great opportunity for scientists. The Yahoo Flickr Creative Commons 100 Million (YFCC100M) dataset comprises 99 million images and nearly 800 thousand videos from Flickr, all shared under Creative Commons licenses. To enable scientists to leverage these media records for field studies, we propose a new framework that extracts targeted subcorpora from the YFCC100M, in a format usable by researchers who are not experts in big data retrieval and processing.

show abstract

Section: Interaction Training For Ai Systemsmentioning

confidence: 99%