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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-bn2018/09/15 20:59:552430------18.81- 0.00 0.00SMTNoSMT system with KENLM Language model
2NICT-5INDICen-bn2018/08/22 19:01:382058------14.55- 0.00 0.00NMTNoBilingual transformer model
3IITP-MTINDICen-bn2018/09/14 20:15:112353------13.27- 0.00 0.00NMTNoTransformer multilingual En-XX
4cvitINDICen-bn2019/03/14 23:16:082641------12.26- 0.00 0.00NMTYesmassive-multi + ft
5ORGANIZERINDICen-bn2018/08/24 18:18:592145------11.58- 0.00 0.00NMTNoone2multi multilingual NMT with Attention
6AnuvaadINDICen-bn2018/09/16 06:56:032449------11.34- 0.00 0.00SMTNoSMT with KenLM
7ORGANIZERINDICen-bn2018/08/29 14:08:172186------11.04- 0.00 0.00NMTNomulti2multi multilingual NMT with Attention
8RGNLPINDICen-bn2018/09/15 20:35:122423------10.98- 0.00 0.00NMTNoNMT system with a 2-layer LSTM method
9ORGANIZERINDICen-bn2018/08/20 11:06:542001------10.68- 0.00 0.00NMTNoNMT with Attention
10NICT-5INDICen-bn2018/08/22 19:02:192059------10.45- 0.00 0.00NMTNoEn-XX transformer model
11NICT-5INDICen-bn2018/08/24 14:58:152127------10.39- 0.00 0.00NMTNoXX-XX transformer model
12cvitINDICen-bn2019/03/14 23:15:252640------10.21- 0.00 0.00NMTYesmassive-multi

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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
1cvitINDICen-bn2019/03/14 23:16:082641------0.654716-0.0000000.000000NMTYesmassive-multi + ft
2RGNLPINDICen-bn2018/09/15 20:59:552430------0.646466-0.0000000.000000SMTNoSMT system with KENLM Language model
3IITP-MTINDICen-bn2018/09/14 20:15:112353------0.637276-0.0000000.000000NMTNoTransformer multilingual En-XX
4NICT-5INDICen-bn2018/08/22 19:01:382058------0.635200-0.0000000.000000NMTNoBilingual transformer model
5NICT-5INDICen-bn2018/08/24 14:58:152127------0.634359-0.0000000.000000NMTNoXX-XX transformer model
6cvitINDICen-bn2019/03/14 23:15:252640------0.632282-0.0000000.000000NMTYesmassive-multi
7ORGANIZERINDICen-bn2018/08/29 14:08:172186------0.625881-0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
8NICT-5INDICen-bn2018/08/22 19:02:192059------0.623997-0.0000000.000000NMTNoEn-XX transformer model
9ORGANIZERINDICen-bn2018/08/24 18:18:592145------0.617890-0.0000000.000000NMTNoone2multi multilingual NMT with Attention
10AnuvaadINDICen-bn2018/09/16 06:56:032449------0.601570-0.0000000.000000SMTNoSMT with KenLM
11ORGANIZERINDICen-bn2018/08/20 11:06:542001------0.598169-0.0000000.000000NMTNoNMT with Attention
12RGNLPINDICen-bn2018/09/15 20:35:122423------0.584339-0.0000000.000000NMTNoNMT system with a 2-layer LSTM method

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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
1cvitINDICen-bn2019/03/14 23:16:082641------0.576480-0.0000000.000000NMTYesmassive-multi + ft
2RGNLPINDICen-bn2018/09/15 20:59:552430------0.570070-0.0000000.000000SMTNoSMT system with KENLM Language model
3cvitINDICen-bn2019/03/14 23:15:252640------0.568830-0.0000000.000000NMTYesmassive-multi
4IITP-MTINDICen-bn2018/09/14 20:15:112353------0.562640-0.0000000.000000NMTNoTransformer multilingual En-XX
5NICT-5INDICen-bn2018/08/22 19:01:382058------0.559620-0.0000000.000000NMTNoBilingual transformer model
6NICT-5INDICen-bn2018/08/22 19:02:192059------0.557310-0.0000000.000000NMTNoEn-XX transformer model
7NICT-5INDICen-bn2018/08/24 14:58:152127------0.541780-0.0000000.000000NMTNoXX-XX transformer model
8ORGANIZERINDICen-bn2018/08/29 14:08:172186------0.538890-0.0000000.000000NMTNomulti2multi multilingual NMT with Attention
9AnuvaadINDICen-bn2018/09/16 06:56:032449------0.532680-0.0000000.000000SMTNoSMT with KenLM
10ORGANIZERINDICen-bn2018/08/24 18:18:592145------0.528720-0.0000000.000000NMTNoone2multi multilingual NMT with Attention
11ORGANIZERINDICen-bn2018/08/20 11:06:542001------0.521130-0.0000000.000000NMTNoNMT with Attention
12RGNLPINDICen-bn2018/09/15 20:35:122423------0.519080-0.0000000.000000NMTNoNMT system with a 2-layer LSTM method

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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

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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