Papers by Kyubyong Park
K-HATERS: A Hate Speech Detection Corpus in Korean with Target-Specific Ratings (2023.findings-emnlp)
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| Challenge: | Existing datasets on hate speech detection focus on overt forms of hate . however, a majority of these resources are English-centric, focusing on overtones of hate. |
| Approach: | They propose a new corpus for hate speech detection in Korean with target-specific offensiveness ratings that offer a three-point Likert scale. |
| Outcome: | The proposed corpus is the largest offensive language corpus in Korean and offers target-specific ratings on a three-point Likert scale. |
Jejueo Datasets for Machine Translation and Speech Synthesis (2020.lrec-1)
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| Challenge: | Jejueo, or the Jeju language, is a minority language used on Jeju Island . there have been many efforts to revitalize the language, but few computational approaches have been used to solve its problems. |
| Approach: | They construct two new Jejueo datasets using interviews and transcripts . they build machine translation and speech synthesis using these datasets based on their results . |
| Outcome: | The proposed datasets will attract interest of both language and machine learning communities. |
KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding (2020.findings-emnlp)
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| Challenge: | Existing benchmark datasets for natural language inference and semantic textual similarity (STS) are not available in the Korean language. |
| Approach: | They construct and release new datasets for Korean NLI and STS . they machine-translate existing English training sets and manually translate development and test sets into Korean to accelerate research on Korean NLU. |
| Outcome: | The proposed datasets are available at https://github.com/kakaobrain/KorNLUDatasets. |
word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs (2020.lrec-1)
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| Challenge: | Our dataset provides top-k word translations in 3,564 (directed) language pairs across 62 languages in OpenSubtitles2018. |
| Approach: | They propose a dataset and an open-source Python package for cross-lingual word translations extracted from sentence-level parallel corpora. |
| Outcome: | The proposed bilingual lexicons have high coverage and achieve competitive translation quality for several language pairs. |
An Empirical Study of Tokenization Strategies for Various Korean NLP Tasks (2020.aacl-main)
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| Challenge: | Traditionally, tokenization is the very first step in most text processing works. |
| Approach: | They propose to use morphological segmentation followed by BPE for Korean NLP tasks . they empirically examine what is the best tokenization strategy for Korean to/from English . |
| Outcome: | The proposed approach is best for Korean to/from English machine translation and natural language understanding tasks. |