ChineseNLP

Chinese Transliteration

Background

Transliteration translates proper names and technical terms across languages that use different alphabets and sound systems.

Example input/output

Input:

约翰伍兹 (yue han wu zi)

Output:

John Woods

Standard Metrics

• Word Accuracy in Top-1 (ACC) measures correctness of the first transliteration candidate in a candidate list produced by a transliteration system.
• Fuzziness in Top-1 (Mean F-score).
• Mean Reciprocal Rank (MRR).
• MAP measures precision in the n-best candidates for i-th source name, for which reference transliterations are available.

NEWS 2018 Dataset_03.

Named Entity Workshop (NEWS) is a long-running transliteration evaluation campaign. Chinese/English is one of the most popular NEWS language pairs. For NEWS 2018:

• The shared-task report is in http://aclweb.org/anthology/W18-2409.
• The data is described http://workshop.colips.org/news2018/dataset.html.

Test set name	Source	Target	Test set size (phrase pairs)
NEWS 2018 Dataset_03 T-EnCh	English	Chinese	1000
NEWS 2018 Dataset_03 B-ChEn	Chinese	English	1000

Results

English-Chinese

	ACC	F-score	MRR	MAP
He, Cohen (2020)	0.299	0.6799
EDI (University of Edinburgh)	0.304	0.6791	0.4364	0.304

Chinese-English

	ACC	F-score	MRR	MAP
UALB (University of Alberta)	0.3	0.8	0.374	0.3
EDI (University of Edinburgh)	0.276	0.83	0.386	0.276

Resources

• NEWS 2018 also releases training and development data for English-Chinese and Chinese-English.

Train set name	Source	Target	Train set size (phrase pairs)
NEWS 2018 Dataset_03 T-EnCh	English	Chinese	41318
NEWS 2018 Dataset_03 B-ChEn	Chinese	English	32002

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• TRANSLIT: A Large-scale Name Transliteration Resource
  • Dataset for transliteration of person names and geolocations
  • Contains about 1.6 million entries in more than 180 languages (including Chinese), and approx. 3 million name variations.
  • Project link
  • Paper

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