  This paper investigates how linguistic knowledge mined from large text
corpora can aid the generation of natural language descriptions of videos.
Specifically, we integrate both a neural language model and distributional
semantics trained on large text corpora into a recent LSTM-based architecture
for video description. We evaluate our approach on a collection of Youtube
videos as well as two large movie description datasets showing significant
improvements in grammaticality while modestly improving descriptive quality.
