BehancePR: A Punctuation Restoration Dataset for Livestreaming Video Transcript

Anonymous

Paper Link: https://openreview.net/forum?id=t6XXc19YlQp

Paper Type: Short paper (up to four pages of content + unlimited references and appendices)

Abstract: 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 like Stanford Stanza, Spacy, and Trankit underperform on detecting sentence boundary on non-punctuated transcripts of livestreaming videos. The dataset is publicly accessible at http://github.com/nlp-uoregon/behancepr.

Presentation Mode: This paper will be presented in person in Seattle

Copyright Consent Signature (type Name Or NA If Not Transferrable): VIET DAC LAI

Copyright Consent Name And Address: University of Oregon, 1477 E. 13th Avenue, Eugene, OR 97403, USA