NICT_LOGO.JPG KYOTO-U_LOGO.JPG

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
1NICT-5INDICur-en2018/08/24 15:01:222137---30.84---- 0.00 0.00NMTNoXX-XX transformer model
2NICT-5INDICur-en2018/08/24 14:52:352119---27.88---- 0.00 0.00NMTNoXX-En transformer model
3NICT-5INDICur-en2018/09/07 14:33:022243---26.73---- 0.00 0.00NMTNoUnified Source vocabulary by orthography mapping. XX-EN model.
4IITP-MTINDICur-en2018/09/14 19:57:552351---26.56---- 0.00 0.00NMTNoTransformer multilingual XX-En
5cvitINDICur-en2019/03/23 12:53:222665---25.57---- 0.00 0.00NMTYesmassive-multi e270
6cvitINDICur-en2019/03/14 22:12:492628---24.60---- 0.00 0.00NMTYesmassive-multi + ft
7cvitINDICur-en2019/03/22 05:47:102657---24.59---- 0.00 0.00NMTYesmay to en (Transformer) - detokenized
8cvitINDICur-en2019/03/22 05:32:542651---24.36---- 0.00 0.00NMTNomany to en (Transformer)
9cvitINDICur-en2019/03/14 21:55:152621---21.03---- 0.00 0.00NMTYesmassive-multi
10NICT-5INDICur-en2018/08/24 14:52:202118---20.65---- 0.00 0.00NMTNoBilingual transformer model
11ORGANIZERINDICur-en2018/08/24 14:40:532103---19.60---- 0.00 0.00NMTNomulti2one multilingual NMT with Attention
12ORGANIZERINDICur-en2018/08/29 14:35:462197---18.69---- 0.00 0.00NMTNomulti2multi multilingual NMT with Attention
13AnuvaadINDICur-en2018/09/15 18:06:082411---18.31---- 0.00 0.00SMTNoSMT XX-En
14AnuvaadINDICur-en2018/09/15 17:51:202401---18.03---- 0.00 0.00SMTNoSMT with KenLM
15RGNLPINDICur-en2018/09/15 02:54:012379---15.36---- 0.00 0.00SMTNoSMT system with SRILM Language model
16RGNLPINDICur-en2018/09/15 02:42:142372---14.88---- 0.00 0.00SMTNoSMT system with KENLM Language model
17RGNLPINDICur-en2018/09/15 03:19:362386---10.65---- 0.00 0.00NMTNoNMT system with a 2-layer LSTM method
18ORGANIZERINDICur-en2018/08/20 11:25:272012--- 9.29---- 0.00 0.00NMTNoNMT with Attention

Notice:

Back to top

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
1cvitINDICur-en2019/03/22 05:47:102657---0.751459----0.0000000.000000NMTYesmay to en (Transformer) - detokenized
2cvitINDICur-en2019/03/22 05:32:542651---0.746742----0.0000000.000000NMTNomany to en (Transformer)
3cvitINDICur-en2019/03/23 12:53:222665---0.744835----0.0000000.000000NMTYesmassive-multi e270
4NICT-5INDICur-en2018/08/24 15:01:222137---0.742376----0.0000000.000000NMTNoXX-XX transformer model
5cvitINDICur-en2019/03/14 22:12:492628---0.741251----0.0000000.000000NMTYesmassive-multi + ft
6IITP-MTINDICur-en2018/09/14 19:57:552351---0.733161----0.0000000.000000NMTNoTransformer multilingual XX-En
7cvitINDICur-en2019/03/14 21:55:152621---0.719253----0.0000000.000000NMTYesmassive-multi
8ORGANIZERINDICur-en2018/08/24 14:40:532103---0.714075----0.0000000.000000NMTNomulti2one multilingual NMT with Attention
9NICT-5INDICur-en2018/08/24 14:52:352119---0.705470----0.0000000.000000NMTNoXX-En transformer model
10NICT-5INDICur-en2018/09/07 14:33:022243---0.696801----0.0000000.000000NMTNoUnified Source vocabulary by orthography mapping. XX-EN model.
11ORGANIZERINDICur-en2018/08/29 14:35:462197---0.695015----0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
12AnuvaadINDICur-en2018/09/15 18:06:082411---0.635688----0.0000000.000000SMTNoSMT XX-En
13NICT-5INDICur-en2018/08/24 14:52:202118---0.631710----0.0000000.000000NMTNoBilingual transformer model
14AnuvaadINDICur-en2018/09/15 17:51:202401---0.630810----0.0000000.000000SMTNoSMT with KenLM
15RGNLPINDICur-en2018/09/15 03:19:362386---0.619906----0.0000000.000000NMTNoNMT system with a 2-layer LSTM method
16RGNLPINDICur-en2018/09/15 02:54:012379---0.617035----0.0000000.000000SMTNoSMT system with SRILM Language model
17ORGANIZERINDICur-en2018/08/20 11:25:272012---0.611354----0.0000000.000000NMTNoNMT with Attention
18RGNLPINDICur-en2018/09/15 02:42:142372---0.605664----0.0000000.000000SMTNoSMT system with KENLM Language model

Notice:

Back to top

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
1NICT-5INDICur-en2018/08/24 15:01:222137---0.595450----0.0000000.000000NMTNoXX-XX transformer model
2IITP-MTINDICur-en2018/09/14 19:57:552351---0.583910----0.0000000.000000NMTNoTransformer multilingual XX-En
3cvitINDICur-en2019/03/23 12:53:222665---0.578870----0.0000000.000000NMTYesmassive-multi e270
4cvitINDICur-en2019/03/22 05:32:542651---0.571530----0.0000000.000000NMTNomany to en (Transformer)
5cvitINDICur-en2019/03/22 05:47:102657---0.571530----0.0000000.000000NMTYesmay to en (Transformer) - detokenized
6cvitINDICur-en2019/03/14 22:12:492628---0.566190----0.0000000.000000NMTYesmassive-multi + ft
7NICT-5INDICur-en2018/09/07 14:33:022243---0.561620----0.0000000.000000NMTNoUnified Source vocabulary by orthography mapping. XX-EN model.
8NICT-5INDICur-en2018/08/24 14:52:352119---0.555430----0.0000000.000000NMTNoXX-En transformer model
9cvitINDICur-en2019/03/14 21:55:152621---0.544170----0.0000000.000000NMTYesmassive-multi
10AnuvaadINDICur-en2018/09/15 17:51:202401---0.541890----0.0000000.000000SMTNoSMT with KenLM
11RGNLPINDICur-en2018/09/15 02:54:012379---0.541650----0.0000000.000000SMTNoSMT system with SRILM Language model
12RGNLPINDICur-en2018/09/15 02:42:142372---0.537230----0.0000000.000000SMTNoSMT system with KENLM Language model
13ORGANIZERINDICur-en2018/08/24 14:40:532103---0.532100----0.0000000.000000NMTNomulti2one multilingual NMT with Attention
14ORGANIZERINDICur-en2018/08/29 14:35:462197---0.523780----0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
15AnuvaadINDICur-en2018/09/15 18:06:082411---0.519810----0.0000000.000000SMTNoSMT XX-En
16NICT-5INDICur-en2018/08/24 14:52:202118---0.481800----0.0000000.000000NMTNoBilingual transformer model
17RGNLPINDICur-en2018/09/15 03:19:362386---0.468360----0.0000000.000000NMTNoNMT system with a 2-layer LSTM method
18ORGANIZERINDICur-en2018/08/20 11:25:272012---0.427350----0.0000000.000000NMTNoNMT with Attention

Notice:

Back to top

HUMAN (WAT2019)


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

Notice:
Back to top

HUMAN (WAT2018)


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

Notice:
Back to top

HUMAN (WAT2017)


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

Notice:
Back to top

HUMAN (WAT2016)


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

Notice:
Back to top

HUMAN (WAT2015)


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

Notice:
Back to top

HUMAN (WAT2014)


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

Notice:
Back to top

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