LR-Sum: Summarization for Less-Resourced Languages

December 19, 2022 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Chester Palen-Michel, Constantine Lignos arXiv ID 2212.09674 Category cs.CL: Computation & Language Citations 7 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
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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