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    <titleInfo>
        <title>Jejueo Datasets for Machine Translation and Speech Synthesis</title>
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    <name type="personal">
        <namePart type="given">Kyubyong</namePart>
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        <namePart type="given">Joong</namePart>
        <namePart type="family">Choe</namePart>
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    <name type="personal">
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            <title>Proceedings of the Twelfth Language Resources and Evaluation Conference</title>
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    <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.</abstract>
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%0 Conference Proceedings
%T Jejueo Datasets for Machine Translation and Speech Synthesis
%A Park, Kyubyong
%A Choe, Yo Joong
%A Ham, Jiyeon
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F park-etal-2020-jejueo
%X 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.
%U https://aclanthology.org/2020.lrec-1.318
%P 2615-2621

Markdown (Informal)

[Jejueo Datasets for Machine Translation and Speech Synthesis](https://aclanthology.org/2020.lrec-1.318) (Park et al., LREC 2020)

• Jejueo Datasets for Machine Translation and Speech Synthesis (Park et al., LREC 2020)

ACL

• Kyubyong Park, Yo Joong Choe, and Jiyeon Ham. 2020. Jejueo Datasets for Machine Translation and Speech Synthesis. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 2615–2621, Marseille, France. European Language Resources Association.