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WAT

The Workshop on Asian Translation
Evaluation Results

[EVALUATION RESULTS TOP] | [BLEU] | [RIBES] | [AMFM] | [HUMAN (WAT2022)] | [HUMAN (WAT2021)] | [HUMAN (WAT2020)] | [HUMAN (WAT2019)] | [HUMAN (WAT2018)] | [HUMAN (WAT2017)] | [HUMAN (WAT2016)] | [HUMAN (WAT2015)] | [HUMAN (WAT2014)] | [EVALUATION RESULTS USAGE POLICY]

BLEU


# Team Task Date/Time DataID BLEU
Method
Other
Resources
System
Description
juman kytea mecab moses-
tokenizer
stanford-
segmenter-
ctb
stanford-
segmenter-
pku
indic-
tokenizer
unuse myseg kmseg
1NTTTDDCTXTja-en2019/07/22 14:39:282800---55.26------NMTNoTransformer Big Single
2sarahTDDCTXTja-en2019/07/22 16:19:172808---58.38------NMTNoTransformer, ensemble of 4 models
3NTTTDDCTXTja-en2019/07/22 16:19:352809---58.91------NMTNoTransformer Big Single Fine-tuned with items data
4sarahTDDCTXTja-en2019/07/22 16:24:032812---54.84------NMTNoTransformer, single model
5NTTTDDCTXTja-en2019/07/23 13:04:462852---60.48------NMTNoTransformer Big Single Fine-tuned with items data 4 models ensemble
6NTTTDDCTXTja-en2019/07/26 13:56:373005---61.19------NMTNoTransformer Big Single Fine-tuned with items data R2L re-ranking 4 models ensemble
7NICT-2TDDCTXTja-en2019/07/26 22:28:223083---55.28------NMTNoTransformer, single model w/ long warm-up
8NICT-2TDDCTXTja-en2019/07/26 22:30:033084---56.95------NMTNoTransformer, ensemble of 4 models w/ long warm-up
9geoduckTDDCTXTja-en2019/07/27 14:13:283200---61.38------OtherYesTM + NMT (a single Transformer)
10geoduckTDDCTXTja-en2019/07/27 16:44:463217---51.08------OtherYesTM + MT (ensemble)
11ORGANIZERTDDCTXTja-en2019/08/02 16:46:453263---24.11------NMTNobaseline using OpenNMT
12ORGANIZERTDDCTXTja-en2019/08/02 16:56:333265---25.37------OtherYesAzure Custom Translator

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RIBES


# Team Task Date/Time DataID RIBES
Method
Other
Resources
System
Description
juman kytea mecab moses-
tokenizer
stanford-
segmenter-
ctb
stanford-
segmenter-
pku
indic-
tokenizer
unuse myseg kmseg
1NTTTDDCTXTja-en2019/07/22 14:39:282800---0.839808------NMTNoTransformer Big Single
2sarahTDDCTXTja-en2019/07/22 16:19:172808---0.865364------NMTNoTransformer, ensemble of 4 models
3NTTTDDCTXTja-en2019/07/22 16:19:352809---0.851833------NMTNoTransformer Big Single Fine-tuned with items data
4sarahTDDCTXTja-en2019/07/22 16:24:032812---0.845921------NMTNoTransformer, single model
5NTTTDDCTXTja-en2019/07/23 13:04:462852---0.858363------NMTNoTransformer Big Single Fine-tuned with items data 4 models ensemble
6NTTTDDCTXTja-en2019/07/26 13:56:373005---0.861346------NMTNoTransformer Big Single Fine-tuned with items data R2L re-ranking 4 models ensemble
7NICT-2TDDCTXTja-en2019/07/26 22:28:223083---0.840931------NMTNoTransformer, single model w/ long warm-up
8NICT-2TDDCTXTja-en2019/07/26 22:30:033084---0.848530------NMTNoTransformer, ensemble of 4 models w/ long warm-up
9geoduckTDDCTXTja-en2019/07/27 14:13:283200---0.850551------OtherYesTM + NMT (a single Transformer)
10geoduckTDDCTXTja-en2019/07/27 16:44:463217---0.659190------OtherYesTM + MT (ensemble)
11ORGANIZERTDDCTXTja-en2019/08/02 16:46:453263---0.701005------NMTNobaseline using OpenNMT
12ORGANIZERTDDCTXTja-en2019/08/02 16:56:333265---0.725205------OtherYesAzure Custom Translator

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AMFM


# Team Task Date/Time DataID AMFM
Method
Other
Resources
System
Description
unuse unuse unuse unuse unuse unuse unuse unuse unuse unuse
1NTTTDDCTXTja-en2019/07/22 14:39:282800---0.727530------NMTNoTransformer Big Single
2sarahTDDCTXTja-en2019/07/22 16:19:172808---0.745110------NMTNoTransformer, ensemble of 4 models
3NTTTDDCTXTja-en2019/07/22 16:19:352809---0.742730------NMTNoTransformer Big Single Fine-tuned with items data
4sarahTDDCTXTja-en2019/07/22 16:24:032812---0.732790------NMTNoTransformer, single model
5NTTTDDCTXTja-en2019/07/23 13:04:462852---0.749680------NMTNoTransformer Big Single Fine-tuned with items data 4 models ensemble
6NTTTDDCTXTja-en2019/07/26 13:56:373005---0.753630------NMTNoTransformer Big Single Fine-tuned with items data R2L re-ranking 4 models ensemble
7NICT-2TDDCTXTja-en2019/07/26 22:28:223083---0.732660------NMTNoTransformer, single model w/ long warm-up
8NICT-2TDDCTXTja-en2019/07/26 22:30:033084---0.744390------NMTNoTransformer, ensemble of 4 models w/ long warm-up
9geoduckTDDCTXTja-en2019/07/27 14:13:283200---0.743820------OtherYesTM + NMT (a single Transformer)
10geoduckTDDCTXTja-en2019/07/27 16:44:463217---0.623770------OtherYesTM + MT (ensemble)
11ORGANIZERTDDCTXTja-en2019/08/02 16:46:453263---0.583850------NMTNobaseline using OpenNMT
12ORGANIZERTDDCTXTja-en2019/08/02 16:56:333265---0.602290------OtherYesAzure Custom Translator

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HUMAN (WAT2022)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2021)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2020)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2019)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description
1NTTTDDCTXTja-en2019/07/26 13:56:37300555.500NMTNoTransformer Big Single Fine-tuned with items data R2L re-ranking 4 models ensemble
2sarahTDDCTXTja-en2019/07/22 16:19:17280849.500NMTNoTransformer, ensemble of 4 models
3NICT-2TDDCTXTja-en2019/07/26 22:30:03308449.000NMTNoTransformer, ensemble of 4 models w/ long warm-up
4sarahTDDCTXTja-en2019/07/22 16:24:03281237.750NMTNoTransformer, single model
5geoduckTDDCTXTja-en2019/07/27 14:13:28320030.000OtherYesTM + NMT (a single Transformer)
6geoduckTDDCTXTja-en2019/07/27 16:44:463217-28.250OtherYesTM + MT (ensemble)

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HUMAN (WAT2018)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2017)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2016)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2015)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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HUMAN (WAT2014)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description

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EVALUATION RESULTS USAGE POLICY

When you use the WAT evaluation results for any purpose such as:
- writing technical papers,
- making presentations about your system,
- advertising your MT system to the customers,
you can use the information about translation directions, scores (including both automatic and human evaluations) and ranks of your system among others. You can also use the scores of the other systems, but you MUST anonymize the other system's names. In addition, you can show the links (URLs) to the WAT evaluation result pages.

NICT (National Institute of Information and Communications Technology)
Kyoto University
Last Modified: 2018-08-02