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.