Call for Paper: 1st workshop on Transcript Understanding

Venue: COLING 2022

Location: Gyeongju, Republic of Korea

Submission deadline: August 1, 2022

Submission Site: https://www.softconf.com/coling2022/TU https://www.softconf.com/coling2022/TU

Workshop Website: https://tuworkshop.github.io https://tuworkshop.github.io/

Overview:

Videos have become an omnipresent source of knowledge: courses, presentations, conferences, documentaries, livestreams, meeting recordings, vlogs. This has created a strong demand for transcript understanding. However, the quality of audio and video content shared online and the nature of speech, video transcripts pose many challenges to the existing natural language processing technologies.

At the First workshop on Transcript Understanding (TU@COLING2022), we aim to bring together researchers from various domains to make the best of the knowledge that all these videos contain. Researchers from related domains are invited to paper on recent advanced technologies, resources, tools, and challenges for Transcript Understanding.

Topics:

The TU workshop holds a research track and a shared task track. The research track aims to explore recent advances and remaining challenges on video transcript understanding. As this topic is a multi-modal subject, researchers from artificial intelligence, computer vision, speech processing, natural language processing, data mining, statistics, and other fields are invited to submit papers on recent advances, resources, tools, challenges for video transcript understanding. To this end, the topics of the workshop include but are not limited to the following:

- Fundamental processing for video transcript, such as punctuation restoration, chunking, parsing, and named entity recognition. - Subtitle segmentation - Text summarization and keyword extraction for transcripts - Event extraction, intent detection, and slot filling - Sentiment analysis for speech text processing - Noisy text processing - Fact-checking, evidence extraction - Question-Answering extraction from transcripts - Automatic Speech Recognition, and related system such as speaker identification and filler word detection - Multi-modal, multilingual video-speech-text processing

Important Dates

Papers Due (extended): Aug 1, 2022 (Monday) Notification of Acceptance: August 22, 2022 (Monday) Camera-ready papers due: September 5, 2022 (Monday) Workshop proceedings due: September 19, 2022 (Monday) Workshop date: October 17, 2022

All deadlines are “anywhere on earth” (UTC-12)

Submissions:

Authors are invited to submit their unpublished work that represents novel research. The papers should be written in English using the *ACL style. Authors can also submit the supplementary materials, including technical appendices, source codes, datasets, and multimedia appendices. All submissions, including the main paper and its supplementary materials, should be fully anonymized. For more information on formatting and anonymity guidelines, please refer to COLING 2022 submission guidelines.

TU accepts both long papers (8 pages) and short papers (4 pages). The paper can include unlimited appendix and references. Upon the acceptance, the authors are provided with 1 more page to address the reviewer comments.

All papers will be double blind peer reviewed. Two reviewers with the same technical expertise will review each paper. Authors of the accepted papers will present their work in either the Oral or Poster session. All accepted papers will appear on the workshop proceedings that will be published on CEUR-WS. The authors will keep the copyright of their papers that are published on CEUR-WS. The workshop proceedings will be indexed by DBLP.

Both research paper and shared task paper must be submitted using SoftConf at https://www.softconf.com/coling2022/TU/ https://www.softconf.com/coling2022/TU/.

We look forward to seeing you all at the virtual conference.

TU@COLING2022 Organizers: Franck Dernoncourt (Adobe Research, USA) Thien Huu Nguyen (University of Oregon, USA) Viet Dac Lai (University of Oregon, USA) Amir Pouran Ben Veyseh (University of Oregon, USA)