  Given the increasing number of livestreaming videos, automatic speech
recognition and post-processing for livestreaming video transcripts are crucial
for efficient data management as well as knowledge mining. A key step in this
process is punctuation restoration which restores fundamental text structures
such as phrase and sentence boundaries from the video transcripts. This work
presents a new human-annotated corpus, called BehancePR, for punctuation
restoration in livestreaming video transcripts. Our experiments on BehancePR
demonstrate the challenges of punctuation restoration for this domain.
Furthermore, we show that popular natural language processing toolkits are
incapable of detecting sentence boundary on non-punctuated transcripts of
livestreaming videos, calling for more research effort to develop robust models
for this area.
