  Keyphrase extraction is one of the essential tasks for document understanding
in NLP. While the majority of the prior works are dedicated to the formal
setting, e.g., books, news or web-blogs, informal texts such as video
transcripts are less explored. To address this limitation, in this work we
present a novel corpus and method for keyphrase extraction from the transcripts
of the videos streamed on the Behance platform. More specifically, in this
work, a novel data augmentation is proposed to enrich the model with the
background knowledge about the keyphrase extraction task from other domains.
Extensive experiments on the proposed dataset dataset show the effectiveness of
the introduced method.
