Jejueo Datasets for Machine Translation and Speech Synthesis

Kyubyong Park, Yo Joong Choe, Jiyeon Ham


Abstract
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.
Anthology ID:
2020.lrec-1.318
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2615–2621
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.318
DOI:
Bibkey:
Cite (ACL):
Kyubyong Park, Yo Joong Choe, and Jiyeon Ham. 2020. Jejueo Datasets for Machine Translation and Speech Synthesis. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 2615–2621, Marseille, France. European Language Resources Association.
Cite (Informal):
Jejueo Datasets for Machine Translation and Speech Synthesis (Park et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.318.pdf
Code
 kakaobrain/jejueo
Data
JIT DatasetJSS Dataset