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Scored Systems
| System | Submitter | System Notes | Constraint | Run Notes | BLEU | BLEU-cased | TER | BEER 2.0 | CharactTER |
|---|---|---|---|---|---|---|---|---|---|
| SogouKnowing-nmt (Details) | Sogou Knowing Sogou |
Ensemble deep NMT models, rerank with NMT right-2-left, t2s model, NGramLM, BPE, etc | yes | Ensemble deep NMT models, rerank with NMT right-2-left, t2s model, NGramLM, BPE, etc |
27.2 |
26.4 |
0.662 |
0.570 |
0.599 |
| xmunmt_ensemble_zh-en (Details) | Zhixing Tan Xiamen University |
Ensemble 4 models, reranked with 1 r2l model, BPE, CWMT+UN+NC, news2016 synthetic | yes |
27.0 |
26.0 |
0.645 |
0.566 |
0.605 |
|
| NRC-2017-zh2en (Details) | NRC-CNRC National Research Council Canada |
yes | BPE, back-translate 20M, finetune with selected data, ensemble 14 NMT models, rerank with IBM models, big LMs, and NNJMs. |
26.9 |
25.8 |
0.662 |
0.562 |
0.632 |
|
| uedin-nmt (Details) | barry University of Edinburgh |
Nematus deep model, layer norm, bpe news2016 synthetic. | yes | Ensemble for 3 l-r, reranked with ensemble of 3 r-l. |
26.6 |
25.7 |
0.657 |
0.565 |
0.616 |
| bit-zhen (Details) | bit-nmt |
yes |
26.7 |
25.6 |
0.631 |
0.568 |
0.620 |
||
| SogouKnowing-nmt (Details) | Sogou Knowing Sogou |
Single deep NMT model, reranked with NMT variants and other featues, BPE, etc. | yes | Single deep NMT model, reranked with NMT variants and other featues, BPE, etc. |
25.2 |
24.0 |
0.679 |
0.557 |
0.680 |
| xmunmt_single_zh-en (Details) | Zhixing Tan Xiamen University |
single model, BPE, CWMT+UN+NC (contrastive) | yes |
24.3 |
23.4 |
0.670 |
0.552 |
0.634 |
|
| rabbit (Details) | rabbit rabbit |
yes |
24.2 |
23.1 |
0.663 |
0.554 |
0.650 |
||
| uedin-nmt (Details) | barry University of Edinburgh |
Nematus deep model, layer norm, bpe, news2016 synthetic. | yes | Single best |
23.8 |
22.9 |
0.680 |
0.551 |
0.636 |
| zhang-zh-en-test (Details) | jingjingz |
no |
24.4 |
22.6 |
0.773 |
0.530 |
0.671 |
||
| zhang-zh-en-test (Details) | jingjingz |
no | 4-base-trans |
24.3 |
22.6 |
0.767 |
0.532 |
0.663 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | big |
24.1 |
22.4 |
0.780 |
0.529 |
0.670 |
|
| CASICT-DCU_NMT (Details) | peerachet Institute Of Computing Technology, Chinese Academy Of Sciences |
Neural Machine Translation (RNNSearch) Training Data : CWMT+WMT (In cooperation with School of Computing, Dublin City University) | yes | NMT, RNNSearch Training Data : CWMT+UN |
23.4 |
22.3 |
0.676 |
0.538 |
0.733 |
| test_zh2en (Details) | serenade Peking University |
yes |
24.0 |
21.8 |
0.673 |
0.545 |
0.642 |
||
| zhang-zh-en-test (Details) | jingjingz |
no | transformer-70050-base/eval-5-emsemble |
23.5 |
21.8 |
0.768 |
0.529 |
0.675 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | avg |
23.4 |
21.7 |
0.770 |
0.529 |
0.674 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 59000 |
23.4 |
21.7 |
0.762 |
0.528 |
0.693 |
|
| test_zh2en (Details) | serenade Peking University |
yes |
23.1 |
21.7 |
0.666 |
0.543 |
0.675 |
||
| test_zh2en (Details) | serenade Peking University |
yes |
23.1 |
21.7 |
0.666 |
0.543 |
0.675 |
||
| zhang-zh-en-test (Details) | jingjingz |
no | merge delete & |
23.4 |
21.7 |
0.764 |
0.531 |
0.674 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 63000 |
23.3 |
21.6 |
0.761 |
0.528 |
0.691 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 58001 |
23.3 |
21.6 |
0.763 |
0.528 |
0.693 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 61000 |
23.2 |
21.5 |
0.761 |
0.527 |
0.696 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 70050 |
23.1 |
21.4 |
0.764 |
0.526 |
0.695 |
|
| afrl-mitll-zhen-opennmt (Details) | jeremy.gwinnup AFRL |
8 ensemble system combination, 4 epochs from 1000 hidden, 600 embedding, brnn and 4 epochs from 500 hidden, 500 embedding, rnn | yes |
22.1 |
21.3 |
failed |
0.539 |
0.660 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | ensemble |
22.7 |
21.0 |
0.776 |
0.525 |
0.687 |
|
| ROCMT (Details) | RocMT University of Rochester |
Single system layer normalization + etc unsupervised word and subword(BPE) segmentation minimum risk tuning rnnlm + kenlm, smt rescoring postprocessing no backtranslations | yes |
21.6 |
20.8 |
0.716 |
0.535 |
0.660 |
|
| jhu-nmt (Details) | sding Johns Hopkins University |
Nematus, BPE, CWMT + UN, 4 ensemble | yes |
21.3 |
20.5 |
0.711 |
0.532 |
0.666 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | transformer-30000 |
21.9 |
20.3 |
0.764 |
0.518 |
0.723 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 200000 |
21.2 |
19.7 |
0.777 |
0.516 |
0.721 |
|
| test_zh2en (Details) | serenade Peking University |
yes |
21.4 |
19.5 |
failed |
0.531 |
0.660 |
||
| NMT Model Average Multi-Cards (Details) | songkai.sk anonymous |
Baseline System | yes |
20.1 |
19.0 |
0.818 |
0.509 |
0.851 |
|
| Oregon State University S (Details) | cosmmb Oregon State University |
two layers NMT, bpe, decoding search | yes |
19.4 |
18.5 |
0.722 |
failed |
failed |
|
| Oregon State University R (Details) | cosmmb Oregon State University |
two layers NMT, bpe, decoding search | yes |
19.2 |
18.4 |
0.722 |
0.519 |
0.687 |
|
| anonymous_test (Details) | heureux |
yes | SMT baseline systems |
18.4 |
17.3 |
0.760 |
0.515 |
0.720 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | merge-trans-seq |
18.5 |
17.0 |
0.852 |
0.492 |
0.759 |
|
| PROMT SMT (Details) | Alex Molchanov PROMT LLC |
no |
17.4 |
16.5 |
0.773 |
0.520 |
0.696 |
||
| test_zh2en (Details) | serenade Peking University |
yes |
17.2 |
16.1 |
0.710 |
0.488 |
0.869 |
||
| UU-HNMT (Details) | gtang Uppsala University |
Helsinki Neural Machine Translation system | yes | HNMT with hybrid encoder and character-level decoder, ensemble of 5 models. |
16.8 |
15.9 |
0.754 |
0.499 |
0.763 |
| NMT Model Average Multi-Cards (Details) | songkai.sk anonymous |
Baseline System | yes |
20.2 |
15.9 |
0.822 |
0.493 |
0.868 |
|
| ParFDA (Details) | bicici |
ParFDA Moses Phrase-based SMT system | yes | zh-en (zh segmented with Stanford segmenter) |
13.3 |
12.4 |
0.839 |
failed |
failed |
| ParFDA (Details) | bicici |
ParFDA Moses Phrase-based SMT system | yes | zh-en (zh segmented with Stanford segmenter, 2.8 million training sentences) |
13.0 |
12.1 |
0.841 |
failed |
failed |
| zhang-zh-en-test (Details) | jingjingz |
no | seq-5-merge |
7.8 |
6.8 |
1.054 |
0.417 |
0.865 |
|
| zhang-zh-en-test (Details) | jingjingz |
no | 60001.seq |
7.8 |
6.8 |
1.059 |
0.417 |
0.867 |
|
| att-rnn (Details) | zzz123 student |
no |
failed |
failed |
failed |
0.000 |
0.000 |