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Machine Translation

Machine translation is the task of translating a sentence in a source language to a different target language.

Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.

One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.

( Image credit: Google seq2seq )

Papers

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Showing 6701–6750 of 10752 papers

TitleStatusHype
Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation—0
Neural Machine Translation by Generating Multiple Linguistic Factors—0
FBK’s Multilingual Neural Machine Translation System for IWSLT 2017—0
CHARCUT: Human-Targeted Character-Based MT Evaluation with Loose DifferencesCode0
Evolution Strategy Based Automatic Tuning of Neural Machine Translation Systems—0
The RWTH Aachen Machine Translation Systems for IWSLT 2017—0
Monolingual Embeddings for Low Resourced Neural Machine TranslationCode0
Domain-independent Punctuation and Segmentation Insertion—0
Toward Robust Neural Machine Translation for Noisy Input Sequences—0
Kyoto University MT System Description for IWSLT 2017—0
Overview of the IWSLT 2017 Evaluation Campaign—0
KIT’s Multilingual Neural Machine Translation systems for IWSLT 2017—0
Towards better translation performance on spoken language—0
Three-phase training to address data sparsity in Neural Machine Translation—0
Deliberation Networks: Sequence Generation Beyond One-Pass Decoding—0
Decoding with Value Networks for Neural Machine Translation—0
SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks—0
Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification—0
IJCNLP-2017 Task 4: Customer Feedback Analysis—0
Learning from Parenthetical Sentences for Term Translation in Machine Translation—0
Book Review: Syntax-Based Statistical Machine Translation by Philip Williams, Rico Sennrich, Matt Post and Philipp Koehn—0
Survey: Multiword Expression Processing: A Survey—0
Deep Learning Scaling is Predictable, Empirically—0
Modeling Coherence for Neural Machine Translation with Dynamic and Topic Caches—0
Parameters Optimization of Deep Learning Models using Particle Swarm Optimization—0
Neural Text Generation: A Practical Guide—0
Population Based Training of Neural NetworksCode1
Modeling Past and Future for Neural Machine TranslationCode0
Learning to Remember Translation History with a Continuous CacheCode0
Machine Translation using Semantic Web Technologies: A Survey—0
Counterfactual Learning for Machine Translation: Degeneracies and Solutions—0
Effective Strategies in Zero-Shot Neural Machine TranslationCode0
Using stochastic computation graphs formalism for optimization of sequence-to-sequence modelCode0
Evaluating Machine Translation Performance on Chinese Idioms with a Blacklist Method—0
E-PUR: An Energy-Efficient Processing Unit for Recurrent Neural Networks—0
Incorporating Syntactic Uncertainty in Neural Machine Translation with Forest-to-Sequence Model—0
An Encoder-Decoder Framework Translating Natural Language to Database Queries—0
ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations—0
Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings—0
Classical Structured Prediction Losses for Sequence to Sequence Learning—0
Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMTCode1
Syntax-Directed Attention for Neural Machine Translation—0
Document Context Neural Machine Translation with Memory Networks—0
Block-Sparse Recurrent Neural Networks—0
Non-Autoregressive Neural Machine TranslationCode0
Weighted Transformer Network for Machine TranslationCode0
A^4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation—0
Synthetic and Natural Noise Both Break Neural Machine TranslationCode0
Towards Neural Machine Translation with Partially Aligned Corpora—0
Compressing Word Embeddings via Deep Compositional Code LearningCode0
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All datasetsWMT2014 English-GermanWMT2014 English-FrenchIWSLT2014 German-EnglishACESWMT2016 English-RomanianWMT2016 Romanian-EnglishWMT2014 German-EnglishIWSLT2015 German-EnglishWMT2016 English-GermanIWSLT2015 English-VietnameseIWSLT2015 English-GermanWMT2016 German-English

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer Cycle (Rev)BLEU score35.14—Unverified
2Noisy back-translationBLEU score35—Unverified
3Transformer+Rep(Uni)BLEU score33.89—Unverified
4T5-11BBLEU score32.1—Unverified
5BiBERTBLEU score31.26—Unverified
6Transformer + R-DropBLEU score30.91—Unverified
7Bi-SimCutBLEU score30.78—Unverified
8BERT-fused NMTBLEU score30.75—Unverified
9Data Diversification - TransformerBLEU score30.7—Unverified
10SimCutBLEU score30.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer+BT (ADMIN init)BLEU score46.4—Unverified
2Noisy back-translationBLEU score45.6—Unverified
3mRASP+Fine-TuneBLEU score44.3—Unverified
4Transformer + R-DropBLEU score43.95—Unverified
5Transformer (ADMIN init)BLEU score43.8—Unverified
6AdminBLEU score43.8—Unverified
7BERT-fused NMTBLEU score43.78—Unverified
8MUSE(Paralllel Multi-scale Attention)BLEU score43.5—Unverified
9T5BLEU score43.4—Unverified
10Local Joint Self-attentionBLEU score43.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PiNMTBLEU score40.43—Unverified
2BiBERTBLEU score38.61—Unverified
3Bi-SimCutBLEU score38.37—Unverified
4Cutoff + Relaxed Attention + LMBLEU score37.96—Unverified
5DRDABLEU score37.95—Unverified
6Transformer + R-Drop + CutoffBLEU score37.9—Unverified
7SimCutBLEU score37.81—Unverified
8Cutoff+KneeBLEU score37.78—Unverified
9CutoffBLEU score37.6—Unverified
10CipherDAugBLEU score37.53—Unverified
#ModelMetricClaimedVerifiedStatus
1HWTSC-Teacher-SimScore19.97—Unverified
2MS-COMET-22Score19.89—Unverified
3MS-COMET-QE-22Score19.76—Unverified
4KG-BERTScoreScore17.28—Unverified
5metricx_xl_DA_2019Score17.17—Unverified
6COMET-QEScore16.8—Unverified
7COMET-22Score16.31—Unverified
8UniTE-srcScore15.68—Unverified
9UniTE-refScore15.38—Unverified
10metricx_xxl_DA_2019Score15.24—Unverified