WikiHan: A New Comparative Dataset for Chinese Languages
Kalvin Chang, Chenxuan Cui, Youngmin Kim, David R. Mortensen
Abstract
Most comparative datasets of Chinese varieties are not digital; however, Wiktionary includes a wealth of transcriptions of words from these varieties. The usefulness of these data is limited by the fact that they use a wide range of variety-specific romanizations, making data difficult to compare. The current work collects this data into a single constituent (IPA, or International Phonetic Alphabet) and structured form (TSV) for use in comparative linguistics and Chinese NLP. At the time of writing, the dataset contains 67,943 entries across 8 varieties and Middle Chinese. The dataset is validated on a protoform reconstruction task using an encoder-decoder cross-attention architecture (Meloni et al 2021), achieving an accuracy of 54.11%, a PER (phoneme error rate) of 17.69%, and a FER (feature error rate) of 6.60%.- Anthology ID:
- 2022.coling-1.314
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 3563–3569
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.314
- DOI:
- Bibkey:
- Cite (ACL):
- Kalvin Chang, Chenxuan Cui, Youngmin Kim, and David R. Mortensen. 2022. WikiHan: A New Comparative Dataset for Chinese Languages. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3563–3569, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- WikiHan: A New Comparative Dataset for Chinese Languages (Chang et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.314.pdf
- Code
- cmu-llab/wikihan + additional community code
Export citation
@inproceedings{chang-etal-2022-wikihan,
title = "{W}iki{H}an: A New Comparative Dataset for {C}hinese Languages",
author = "Chang, Kalvin and
Cui, Chenxuan and
Kim, Youngmin and
Mortensen, David R.",
editor = "Calzolari, Nicoletta and
Huang, Chu-Ren and
Kim, Hansaem and
Pustejovsky, James and
Wanner, Leo and
Choi, Key-Sun and
Ryu, Pum-Mo and
Chen, Hsin-Hsi and
Donatelli, Lucia and
Ji, Heng and
Kurohashi, Sadao and
Paggio, Patrizia and
Xue, Nianwen and
Kim, Seokhwan and
Hahm, Younggyun and
He, Zhong and
Lee, Tony Kyungil and
Santus, Enrico and
Bond, Francis and
Na, Seung-Hoon",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.314",
pages = "3563--3569",
abstract = "Most comparative datasets of Chinese varieties are not digital; however, Wiktionary includes a wealth of transcriptions of words from these varieties. The usefulness of these data is limited by the fact that they use a wide range of variety-specific romanizations, making data difficult to compare. The current work collects this data into a single constituent (IPA, or International Phonetic Alphabet) and structured form (TSV) for use in comparative linguistics and Chinese NLP. At the time of writing, the dataset contains 67,943 entries across 8 varieties and Middle Chinese. The dataset is validated on a protoform reconstruction task using an encoder-decoder cross-attention architecture (Meloni et al 2021), achieving an accuracy of 54.11{\%}, a PER (phoneme error rate) of 17.69{\%}, and a FER (feature error rate) of 6.60{\%}.",
}
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%0 Conference Proceedings %T WikiHan: A New Comparative Dataset for Chinese Languages %A Chang, Kalvin %A Cui, Chenxuan %A Kim, Youngmin %A Mortensen, David R. %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F chang-etal-2022-wikihan %X Most comparative datasets of Chinese varieties are not digital; however, Wiktionary includes a wealth of transcriptions of words from these varieties. The usefulness of these data is limited by the fact that they use a wide range of variety-specific romanizations, making data difficult to compare. The current work collects this data into a single constituent (IPA, or International Phonetic Alphabet) and structured form (TSV) for use in comparative linguistics and Chinese NLP. At the time of writing, the dataset contains 67,943 entries across 8 varieties and Middle Chinese. The dataset is validated on a protoform reconstruction task using an encoder-decoder cross-attention architecture (Meloni et al 2021), achieving an accuracy of 54.11%, a PER (phoneme error rate) of 17.69%, and a FER (feature error rate) of 6.60%. %U https://aclanthology.org/2022.coling-1.314 %P 3563-3569
Markdown (Informal)
[WikiHan: A New Comparative Dataset for Chinese Languages](https://aclanthology.org/2022.coling-1.314) (Chang et al., COLING 2022)
- WikiHan: A New Comparative Dataset for Chinese Languages (Chang et al., COLING 2022)
ACL
- Kalvin Chang, Chenxuan Cui, Youngmin Kim, and David R. Mortensen. 2022. WikiHan: A New Comparative Dataset for Chinese Languages. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3563–3569, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.