Supervised Contrastive Representation Learning for Individual Recognition in the Wild
Date:
Talk title: “Supervised Contrastive Representation Learning for Individual Recognition in the Wild.” On-going reaching into the application of state-of-the-art deep learning techniques for speaker recognition in the wild.
A signaller E at time t produces f(Ct;ϕ) individually distinct cues Ct such as visual, acoustic or olfactory that is propagated in a medium M(Ct). A cue can be uni-modal or multi modal. A receiver E′ perceives g(Cj,Ct;θ) cues through their sensory percepts that are matched against a templating system. A cue is compared with known template T to a determine unique behavioral response directed to the signaller.
