K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866914801260691456 |
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| author | Kim, Haven Jung, Jongmin Jeong, Dasaem Nam, Juhan |
| author_facet | Kim, Haven Jung, Jongmin Jeong, Dasaem Nam, Juhan |
| contents | Lyric translation, a field studied for over a century, is now attracting computational linguistics researchers. We identified two limitations in previous studies. Firstly, lyric translation studies have predominantly focused on Western genres and languages, with no previous study centering on K-pop despite its popularity. Second, the field of lyric translation suffers from a lack of publicly available datasets; to the best of our knowledge, no such dataset exists. To broaden the scope of genres and languages in lyric translation studies, we introduce a novel singable lyric translation dataset, approximately 89\% of which consists of K-pop song lyrics. This dataset aligns Korean and English lyrics line-by-line and section-by-section. We leveraged this dataset to unveil unique characteristics of K-pop lyric translation, distinguishing it from other extensively studied genres, and to construct a neural lyric translation model, thereby underscoring the importance of a dedicated dataset for singable lyric translations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_11093 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling Kim, Haven Jung, Jongmin Jeong, Dasaem Nam, Juhan Computation and Language Machine Learning Multimedia Lyric translation, a field studied for over a century, is now attracting computational linguistics researchers. We identified two limitations in previous studies. Firstly, lyric translation studies have predominantly focused on Western genres and languages, with no previous study centering on K-pop despite its popularity. Second, the field of lyric translation suffers from a lack of publicly available datasets; to the best of our knowledge, no such dataset exists. To broaden the scope of genres and languages in lyric translation studies, we introduce a novel singable lyric translation dataset, approximately 89\% of which consists of K-pop song lyrics. This dataset aligns Korean and English lyrics line-by-line and section-by-section. We leveraged this dataset to unveil unique characteristics of K-pop lyric translation, distinguishing it from other extensively studied genres, and to construct a neural lyric translation model, thereby underscoring the importance of a dedicated dataset for singable lyric translations. |
| title | K-pop Lyric Translation: Dataset, Analysis, and Neural-Modelling |
| topic | Computation and Language Machine Learning Multimedia |
| url | https://arxiv.org/abs/2309.11093 |