  Jejueo was classified as critically endangered by UNESCO in 2010. Although
diverse efforts to revitalize it have been made, there have been few
computational approaches. Motivated by this, we construct two new Jejueo
datasets: Jejueo Interview Transcripts (JIT) and Jejueo Single Speaker Speech
(JSS). The JIT dataset is a parallel corpus containing 170k+ Jejueo-Korean
sentences, and the JSS dataset consists of 10k high-quality audio files
recorded by a native Jejueo speaker and a transcript file. Subsequently, we
build neural systems of machine translation and speech synthesis using them.
All resources are publicly available via our GitHub repository. We hope that
these datasets will attract interest of both language and machine learning
communities.
