  Natural language processing (NLP) has a significant impact on society via
technologies such as machine translation and search engines. Despite its
success, NLP technology is only widely available for high-resource languages
such as English and Chinese, while it remains inaccessible to many languages
due to the unavailability of data resources and benchmarks. In this work, we
focus on developing resources for languages in Indonesia. Despite being the
second most linguistically diverse country, most languages in Indonesia are
categorized as endangered and some are even extinct. We develop the first-ever
parallel resource for 10 low-resource languages in Indonesia. Our resource
includes datasets, a multi-task benchmark, and lexicons, as well as a parallel
Indonesian-English dataset. We provide extensive analyses and describe the
challenges when creating such resources. We hope that our work can spark NLP
research on Indonesian and other underrepresented languages.
