WAT

The Workshop on Asian Translation

Evaluation Results

BLEU

Notice:

This table is sorted by the leftmost segmenters. You can change the segmenter used to sort by clicking each segmenter link.

RIBES

Notice:

This table is sorted by the leftmost segmenters. You can change the segmenter used to sort by clicking each segmenter link.

AMFM

Notice:

This table is sorted by the leftmost segmenters. You can change the segmenter used to sort by clicking each segmenter link.
Adequacy-Fluency Metrics (AMFM) is a two-dimensional automatic evaluation metric for machine translation, designed to operate at the sentence level. It is based on adequacy and fluency, to decouple semantic and syntactic components of the translation process to provide a balanced view on translation quality.
The detail of AMFM is shown on the following paper: "Adequacy–Fluency Metrics: Evaluating MT in the Continuous Space Model Framework" [pdf]. Invited Talk in WAT2015 also helps understanding [slide].

HUMAN (WAT2019)

Notice:

HUMAN (WAT2019) is the result of the Pairwise Crowdsourcing Evaluation on WAT2019.
HUMAN (WAT2019) was evaluated by 5 different workers and the final decision is made by the voting of the judgements.

HUMAN (WAT2018)

Notice:

HUMAN (WAT2018) is the result of the Pairwise Crowdsourcing Evaluation on WAT2018.
HUMAN (WAT2018) was evaluated by 5 different workers and the final decision is made by the voting of the judgements.

HUMAN (WAT2017)

Notice:

HUMAN (WAT2017) is the result of the Pairwise Crowdsourcing Evaluation on WAT2017.
HUMAN (WAT2017) was evaluated by 5 different workers and the final decision is made by the voting of the judgements.

HUMAN (WAT2016)

Notice:

HUMAN (WAT2016) is the result of the Pairwise Crowdsourcing Evaluation on WAT2016.
HUMAN (WAT2016) was evaluated by 5 different workers and the final decision is made by the voting of the judgements.

HUMAN (WAT2015)

Notice:

HUMAN (WAT2015) is the result of the Pairwise Crowdsourcing Evaluation on WAT2015.
HUMAN (WAT2015) was evaluated by 5 different workers and the final decision is made by the voting of the judgements.
The detail of the evaluation can be found in the pdf document (PDF file).

HUMAN (WAT2014)

Notice:

HUMAN (WAT2014) is the result of the Pairwise Crowdsourcing Evaluation on WAT2014.
HUMAN (WAT2014) was evaluated by 3 different workers and the final decision is made by the voting of the judgements.
The detail of the evaluation can be found in the pdf document (PDF file).

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

#	Team	Task	Date/Time	DataID	BLEU										Method	Other Resources	System Description
#	Team	Task	Date/Time	DataID	juman	kytea	mecab	moses- tokenizer	stanford- segmenter- ctb	stanford- segmenter- pku	indic- tokenizer	unuse	myseg	kmseg	Method	Other Resources	System Description
1	IDIAP	MMEVTEXTen-hi	2019/07/25 23:52:34	2956	-	-	-	-	-	-	41.32	-	-	-	NMT	Yes	Transformer base model using IITB Corpus as other resources.
2	ORGANIZER	MMEVTEXTen-hi	2019/07/23 17:00:37	2860	-	-	-	-	-	-	38.95	-	-	-	NMT	No	Transformer base model
3	683	MMEVTEXTen-hi	2019/08/10 02:51:37	3285	-	-	-	-	-	-	38.19	-	-	-	NMT	No	This system is using MarianNMT tool.
4	683	MMEVTEXTen-hi	2019/08/10 03:09:51	3286	-	-	-	-	-	-	25.34	-	-	-	NMT	Yes	Transformer based
5	NITSNLP	MMEVTEXTen-hi	2019/08/10 22:28:45	3299	-	-	-	-	-	-	20.13	-	-	-	NMT	No	Using encoding format BPE text with OpenNMT tool

#	Team	Task	Date/Time	DataID	RIBES										Method	Other Resources	System Description
#	Team	Task	Date/Time	DataID	juman	kytea	mecab	moses- tokenizer	stanford- segmenter- ctb	stanford- segmenter- pku	indic- tokenizer	unuse	myseg	kmseg	Method	Other Resources	System Description
1	IDIAP	MMEVTEXTen-hi	2019/07/25 23:52:34	2956	-	-	-	-	-	-	0.770754	-	-	-	NMT	Yes	Transformer base model using IITB Corpus as other resources.
2	ORGANIZER	MMEVTEXTen-hi	2019/07/23 17:00:37	2860	-	-	-	-	-	-	0.749535	-	-	-	NMT	No	Transformer base model
3	683	MMEVTEXTen-hi	2019/08/10 02:51:37	3285	-	-	-	-	-	-	0.744158	-	-	-	NMT	No	This system is using MarianNMT tool.
4	683	MMEVTEXTen-hi	2019/08/10 03:09:51	3286	-	-	-	-	-	-	0.636152	-	-	-	NMT	Yes	Transformer based
5	NITSNLP	MMEVTEXTen-hi	2019/08/10 22:28:45	3299	-	-	-	-	-	-	0.574366	-	-	-	NMT	No	Using encoding format BPE text with OpenNMT tool

#	Team	Task	Date/Time	DataID	AMFM										Method	Other Resources	System Description
#	Team	Task	Date/Time	DataID	juman	kytea	mecab	moses- tokenizer	stanford- segmenter- ctb	stanford- segmenter- pku	indic- tokenizer	unuse	myseg	kmseg	Method	Other Resources	System Description
1	IDIAP	MMEVTEXTen-hi	2019/07/25 23:52:34	2956	-	-	-	-	-	-	0.784950	-	-	-	NMT	Yes	Transformer base model using IITB Corpus as other resources.
2	683	MMEVTEXTen-hi	2019/08/10 02:51:37	3285	-	-	-	-	-	-	0.763940	-	-	-	NMT	No	This system is using MarianNMT tool.
3	ORGANIZER	MMEVTEXTen-hi	2019/07/23 17:00:37	2860	-	-	-	-	-	-	0.762180	-	-	-	NMT	No	Transformer base model
4	683	MMEVTEXTen-hi	2019/08/10 03:09:51	3286	-	-	-	-	-	-	0.656370	-	-	-	NMT	Yes	Transformer based
5	NITSNLP	MMEVTEXTen-hi	2019/08/10 22:28:45	3299	-	-	-	-	-	-	0.615290	-	-	-	NMT	No	Using encoding format BPE text with OpenNMT tool

WAT The Workshop on Asian Translation Evaluation Results

BLEU

RIBES

AMFM

HUMAN (WAT2019)

HUMAN (WAT2018)

HUMAN (WAT2017)

HUMAN (WAT2016)

HUMAN (WAT2015)

HUMAN (WAT2014)

EVALUATION RESULTS USAGE POLICY

WAT

The Workshop on Asian Translation

Evaluation Results