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WAT

The Workshop on Asian Translation
Evaluation Results

[EVALUATION RESULTS TOP] | [BLEU] | [RIBES] | [AMFM] | [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
1RGNLPINDICen-ta2018/09/15 21:09:102432------30.53- 0.00 0.00SMTNoSMT system with KENLM Language model
2NICT-5INDICen-ta2018/08/24 15:00:052132------20.39- 0.00 0.00NMTNoXX-XX transformer model
3IITP-MTINDICen-ta2018/09/14 20:22:342356------18.81- 0.00 0.00NMTNoTransformer multilingual En-XX
4NICT-5INDICen-ta2018/08/24 14:49:102109------18.60- 0.00 0.00NMTNoEn-XX transformer model
5cvitINDICen-ta2019/03/14 23:09:142637------16.06- 0.00 0.00NMTYesmassive-multi + ft
6ORGANIZERINDICen-ta2018/08/24 18:22:562148------16.05- 0.00 0.00NMTNoone2multi multilingual NMT with Attention
7AnuvaadINDICen-ta2018/09/16 00:50:332443------15.87- 0.00 0.00SMTNoSMT with KenLM
8ORGANIZERINDICen-ta2018/08/29 14:28:422192------15.41- 0.00 0.00NMTNomulti2multi multilingual NMT with Attention
9cvitINDICen-ta2019/03/14 23:07:292636------12.55- 0.00 0.00NMTYesmassive-multi
10RGNLPINDICen-ta2018/09/15 20:39:142425------11.84- 0.00 0.00NMTNoNMT system with a 2-layer LSTM method
11NICT-5INDICen-ta2018/08/24 14:48:472108------ 8.74- 0.00 0.00NMTNoBilingual transformer model
12ORGANIZERINDICen-ta2018/08/20 11:16:172007------ 7.12- 0.00 0.00NMTNoNMT with Attention

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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
1RGNLPINDICen-ta2018/09/15 21:09:102432------0.724780-0.0000000.000000SMTNoSMT system with KENLM Language model
2cvitINDICen-ta2019/03/14 23:09:142637------0.700706-0.0000000.000000NMTYesmassive-multi + ft
3NICT-5INDICen-ta2018/08/24 15:00:052132------0.690652-0.0000000.000000NMTNoXX-XX transformer model
4AnuvaadINDICen-ta2018/09/16 00:50:332443------0.668548-0.0000000.000000SMTNoSMT with KenLM
5cvitINDICen-ta2019/03/14 23:07:292636------0.667053-0.0000000.000000NMTYesmassive-multi
6ORGANIZERINDICen-ta2018/08/29 14:28:422192------0.664354-0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
7IITP-MTINDICen-ta2018/09/14 20:22:342356------0.658740-0.0000000.000000NMTNoTransformer multilingual En-XX
8ORGANIZERINDICen-ta2018/08/24 18:22:562148------0.651935-0.0000000.000000NMTNoone2multi multilingual NMT with Attention
9NICT-5INDICen-ta2018/08/24 14:49:102109------0.649454-0.0000000.000000NMTNoEn-XX transformer model
10RGNLPINDICen-ta2018/09/15 20:39:142425------0.543018-0.0000000.000000NMTNoNMT system with a 2-layer LSTM method
11NICT-5INDICen-ta2018/08/24 14:48:472108------0.499595-0.0000000.000000NMTNoBilingual transformer model
12ORGANIZERINDICen-ta2018/08/20 11:16:172007------0.457948-0.0000000.000000NMTNoNMT with Attention

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AMFM


# Team Task Date/Time DataID AMFM
Method
Other
Resources
System
Description
juman kytea mecab moses-
tokenizer
stanford-
segmenter-
ctb
stanford-
segmenter-
pku
indic-
tokenizer
unuse myseg kmseg
1RGNLPINDICen-ta2018/09/15 21:09:102432------0.786850-0.0000000.000000SMTNoSMT system with KENLM Language model
2cvitINDICen-ta2019/03/14 23:09:142637------0.760910-0.0000000.000000NMTYesmassive-multi + ft
3AnuvaadINDICen-ta2018/09/16 00:50:332443------0.756890-0.0000000.000000SMTNoSMT with KenLM
4NICT-5INDICen-ta2018/08/24 15:00:052132------0.736930-0.0000000.000000NMTNoXX-XX transformer model
5cvitINDICen-ta2019/03/14 23:07:292636------0.725670-0.0000000.000000NMTYesmassive-multi
6ORGANIZERINDICen-ta2018/08/29 14:28:422192------0.711080-0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
7IITP-MTINDICen-ta2018/09/14 20:22:342356------0.710610-0.0000000.000000NMTNoTransformer multilingual En-XX
8ORGANIZERINDICen-ta2018/08/24 18:22:562148------0.706760-0.0000000.000000NMTNoone2multi multilingual NMT with Attention
9NICT-5INDICen-ta2018/08/24 14:49:102109------0.700960-0.0000000.000000NMTNoEn-XX transformer model
10RGNLPINDICen-ta2018/09/15 20:39:142425------0.614090-0.0000000.000000NMTNoNMT system with a 2-layer LSTM method
11NICT-5INDICen-ta2018/08/24 14:48:472108------0.574630-0.0000000.000000NMTNoBilingual transformer model
12ORGANIZERINDICen-ta2018/08/20 11:16:172007------0.545370-0.0000000.000000NMTNoNMT with Attention

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HUMAN (WAT2019)


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

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HUMAN (WAT2018)


# Team Task Date/Time DataID HUMAN
Method
Other
Resources
System
Description
1AnuvaadINDICen-ta2018/09/16 00:50:33244373.750SMTNoSMT with KenLM
2IITP-MTINDICen-ta2018/09/14 20:22:34235666.500NMTNoTransformer multilingual En-XX
3NICT-5INDICen-ta2018/08/24 15:00:05213260.500NMTNoXX-XX transformer model
4NICT-5INDICen-ta2018/08/24 14:49:10210945.250NMTNoEn-XX transformer model

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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