  Memorability determines what evanesces into emptiness, and what worms its way
into the deepest furrows of our minds. It is the key to curating more
meaningful media content as we wade through daily digital torrents. The
Predicting Media Memorability task in MediaEval 2020 aims to address the
question of media memorability by setting the task of automatically predicting
video memorability. Our approach is a multimodal deep learning-based late
fusion that combines visual, semantic, and auditory features. We used audio
gestalt to estimate the influence of the audio modality on overall video
memorability, and accordingly inform which combination of features would best
predict a given video's memorability scores.
