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Natural language processing (NLP) has a significant impact on society viatechnologies such as machine translation and search engines. Despite itssuccess, NLP technology is only widely available for high-resource languagessuch as English and Chinese, while it remains inaccessible to many languagesdue to the unavailability of data resources and benchmarks. In this work, wefocus on developing resources for languages in Indonesia. Despite being thesecond most linguistically diverse country, most languages in Indonesia arecategorized as endangered and some are even extinct. We develop the first-everparallel resource for 10 low-resource languages in Indonesia. Our resourceincludes datasets, a multi-task benchmark, and lexicons, as well as a parallelIndonesian-English dataset. We provide extensive analyses and describe thechallenges when creating such resources. We hope that our work can spark NLPresearch on Indonesian and other underrepresented languages.

NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages