LR-Sum: Summarization for Less-Resourced Languages

• URL: http://arxiv.org/abs/2212.09674v2
• Date: Thu, 26 Oct 2023 19:50:29 GMT
• Title: LR-Sum: Summarization for Less-Resourced Languages
• Authors: Chester Palen-Michel and Constantine Lignos
• Abstract summary: This preprint describes work in progress on LR-Sum, a new permissively-licensed dataset. LR-Sum contains human-written summaries for 40 languages, many of which are less-resourced. The source data is public domain newswire collected from from Voice of America websites, and LR-Sum is released under a Creative Commons license (CC BY 4.0)
• Score: 12.605915166622818
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This preprint describes work in progress on LR-Sum, a new permissively-licensed dataset created with the goal of enabling further research in automatic summarization for less-resourced languages. LR-Sum contains human-written summaries for 40 languages, many of which are less-resourced. We describe our process for extracting and filtering the dataset from the Multilingual Open Text corpus (Palen-Michel et al., 2022). The source data is public domain newswire collected from from Voice of America websites, and LR-Sum is released under a Creative Commons license (CC BY 4.0), making it one of the most openly-licensed multilingual summarization datasets. We describe how we plan to use the data for modeling experiments and discuss limitations of the dataset.

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