VCSUM: A Versatile Chinese Meeting Summarization Dataset

Han Wu; Mingjie Zhan; Haochen Tan; Zhaohui Hou; Ding Liang; Linqi Song

doi:10.18653/v1/2023.findings-acl.377

VCSUM: A Versatile Chinese Meeting Summarization Dataset

Han Wu, Mingjie Zhan, Haochen Tan, Zhaohui Hou, Ding Liang, Linqi Song^*

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data. To this end, we introduce a versatile Chinese meeting summarization dataset, dubbed VCSUM, consisting of 239 real-life meetings, with a total duration of over 230 hours. We claim our dataset is versatile because we provide the annotations of topic segmentation, headlines, segmentation summaries, overall meeting summaries, and salient sentences for each meeting transcript. As such, the dataset can adapt to various summarization tasks or methods, including segmentation-based summarization, multi-granularity summarization and retrieval-then-generate summarization. Our analysis confirms the effectiveness and robustness of VCSUM. We also provide a set of benchmark models regarding different downstream summarization tasks on VCSUM to facilitate further research. The dataset and code will be released at https://github.com/ hahahawu/VCSum. ©2023 Association for Computational Linguistics.

Original language	English
Title of host publication	Findings of the Association for Computational Linguistics, ACL 2023
Editors	Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Publisher	Association for Computational Linguistics
Pages	6065–6079
ISBN (Print)	9781959429623
DOIs	https://doi.org/10.18653/v1/2023.findings-acl.377
Publication status	Published - Jul 2023
Event	61st Annual Meeting of the Association for Computational Linguistics (ACL 2023) - Westin Harbour Castle, Toronto, Canada Duration: 9 Jul 2023 → 14 Jul 2023 https://2023.aclweb.org/ https://aclanthology.org/events/acl-2023/

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)
Abbreviated title	ACL’23
Country/Territory	Canada
City	Toronto
Period	9/07/23 → 14/07/23
Internet address	https://2023.aclweb.org/ https://aclanthology.org/events/acl-2023/

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Wu, H., Zhan, M., Tan, H., Hou, Z., Liang, D., & Song, L. (2023). VCSUM: A Versatile Chinese Meeting Summarization Dataset. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics, ACL 2023 (pp. 6065–6079). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.377

Wu, Han ; Zhan, Mingjie ; Tan, Haochen et al. / VCSUM: A Versatile Chinese Meeting Summarization Dataset. Findings of the Association for Computational Linguistics, ACL 2023. editor / Anna Rogers ; Jordan Boyd-Graber ; Naoaki Okazaki. Association for Computational Linguistics, 2023. pp. 6065–6079 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

@inproceedings{7bcf8af0df624dc2bf81dd68407f90cd,

title = "VCSUM: A Versatile Chinese Meeting Summarization Dataset",

abstract = "Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data. To this end, we introduce a versatile Chinese meeting summarization dataset, dubbed VCSUM, consisting of 239 real-life meetings, with a total duration of over 230 hours. We claim our dataset is versatile because we provide the annotations of topic segmentation, headlines, segmentation summaries, overall meeting summaries, and salient sentences for each meeting transcript. As such, the dataset can adapt to various summarization tasks or methods, including segmentation-based summarization, multi-granularity summarization and retrieval-then-generate summarization. Our analysis confirms the effectiveness and robustness of VCSUM. We also provide a set of benchmark models regarding different downstream summarization tasks on VCSUM to facilitate further research. The dataset and code will be released at https://github.com/ hahahawu/VCSum. {\textcopyright}2023 Association for Computational Linguistics.",

author = "Han Wu and Mingjie Zhan and Haochen Tan and Zhaohui Hou and Ding Liang and Linqi Song",

year = "2023",

month = jul,

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note = "61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), ACL{\textquoteright}23 ; Conference date: 09-07-2023 Through 14-07-2023",

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Wu, H, Zhan, M, Tan, H, Hou, Z, Liang, D & Song, L 2023, VCSUM: A Versatile Chinese Meeting Summarization Dataset. in A Rogers, J Boyd-Graber & N Okazaki (eds), Findings of the Association for Computational Linguistics, ACL 2023. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, pp. 6065–6079, 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), Toronto, Ontario, Canada, 9/07/23. https://doi.org/10.18653/v1/2023.findings-acl.377

VCSUM: A Versatile Chinese Meeting Summarization Dataset. / Wu, Han; Zhan, Mingjie; Tan, Haochen et al.
Findings of the Association for Computational Linguistics, ACL 2023. ed. / Anna Rogers; Jordan Boyd-Graber; Naoaki Okazaki. Association for Computational Linguistics, 2023. p. 6065–6079 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - VCSUM: A Versatile Chinese Meeting Summarization Dataset

AU - Wu, Han

AU - Zhan, Mingjie

AU - Tan, Haochen

AU - Hou, Zhaohui

AU - Liang, Ding

AU - Song, Linqi

PY - 2023/7

Y1 - 2023/7

N2 - Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data. To this end, we introduce a versatile Chinese meeting summarization dataset, dubbed VCSUM, consisting of 239 real-life meetings, with a total duration of over 230 hours. We claim our dataset is versatile because we provide the annotations of topic segmentation, headlines, segmentation summaries, overall meeting summaries, and salient sentences for each meeting transcript. As such, the dataset can adapt to various summarization tasks or methods, including segmentation-based summarization, multi-granularity summarization and retrieval-then-generate summarization. Our analysis confirms the effectiveness and robustness of VCSUM. We also provide a set of benchmark models regarding different downstream summarization tasks on VCSUM to facilitate further research. The dataset and code will be released at https://github.com/ hahahawu/VCSum. ©2023 Association for Computational Linguistics.

AB - Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data. To this end, we introduce a versatile Chinese meeting summarization dataset, dubbed VCSUM, consisting of 239 real-life meetings, with a total duration of over 230 hours. We claim our dataset is versatile because we provide the annotations of topic segmentation, headlines, segmentation summaries, overall meeting summaries, and salient sentences for each meeting transcript. As such, the dataset can adapt to various summarization tasks or methods, including segmentation-based summarization, multi-granularity summarization and retrieval-then-generate summarization. Our analysis confirms the effectiveness and robustness of VCSUM. We also provide a set of benchmark models regarding different downstream summarization tasks on VCSUM to facilitate further research. The dataset and code will be released at https://github.com/ hahahawu/VCSum. ©2023 Association for Computational Linguistics.

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T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics

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PB - Association for Computational Linguistics

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Y2 - 9 July 2023 through 14 July 2023

ER -

Wu H, Zhan M, Tan H, Hou Z, Liang D, Song L. VCSUM: A Versatile Chinese Meeting Summarization Dataset. In Rogers A, Boyd-Graber J, Okazaki N, editors, Findings of the Association for Computational Linguistics, ACL 2023. Association for Computational Linguistics. 2023. p. 6065–6079. (Proceedings of the Annual Meeting of the Association for Computational Linguistics). doi: 10.18653/v1/2023.findings-acl.377

VCSUM: A Versatile Chinese Meeting Summarization Dataset

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