SOTAVerified

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 5851–5900 of 10752 papers

TitleStatusHype
Syntactic Sentence Simplification for French—0
Syntactic SMT Using a Discriminative Text Generation Model—0
Syntactic Structure from Deep Learning—0
Syntactic Well-Formedness Diagnosis and Error-Based Coaching in Computer Assisted Language Learning using Machine Translation—0
Syntax and Semantics in Quality Estimation of Machine Translation—0
Syntax-Augmented Machine Translation using Syntax-Label Clustering—0
Syntax-Aware Complex-Valued Neural Machine Translation—0
Syntax-aware Data Augmentation for Neural Machine Translation—0
Syntax Aware LSTM model for Semantic Role Labeling—0
Syntax-aware Phrase-based Statistical Machine Translation: System Description—0
Syntax-Based Attention Masking for Neural Machine Translation—0
Syntax-based Deep Matching of Short Texts—0
Syntax-based Multi-system Machine Translation—0
Syntax-based Rewriting for Simultaneous Machine Translation—0
Syntax-based Simultaneous Translation through Prediction of Unseen Syntactic Constituents—0
Syntax-Based Word Ordering Incorporating a Large-Scale Language Model—0
Syntax-Directed Attention for Neural Machine Translation—0
Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations—0
Syntax in End-to-End Natural Language Processing—0
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding—0
Syntax Representation in Word Embeddings and Neural Networks -- A Survey—0
Synthesizer: Rethinking Self-Attention for Transformer Models—0
Synthesizing Compound Words for Machine Translation—0
Synthesizing Monolingual Data for Neural Machine Translation—0
Synthetic Cross-language Information Retrieval Training Data—0
Synthetic Data for Neural Machine Translation of Spoken-Dialects—0
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation—0
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation—0
Synthetic Pre-Training Tasks for Neural Machine Translation—0
Synthetic Source Language Augmentation for Colloquial Neural Machine Translation—0
Systematic Comparison of Professional and Crowdsourced Reference Translations for Machine Translation—0
System Combination for Grammatical Error Correction—0
System Combination for Machine Translation through Paraphrasing—0
System Combination of RBMT plus SPE and Preordering plus SMT—0
System Combination Using Joint, Binarised Feature Vectors—0
System Description: Dependency-based Pre-ordering for Japanese-Chinese Machine Translation—0
System Description of bjtu\_nlp Neural Machine Translation System—0
System Description of Supervised and Unsupervised Neural Machine Translation Approaches from ``NL Processing'' Team at DeepHack.Babel Task—0
System Description: The Submission of FOKUS to the WMT 19 Robustness Task—0
Système de traduction automatique neuronale français-mongol (Historique, mise en place et évaluations) (French-Mongolian Neural Machine Translation System (History, Implementation, and evaluations) Machine Translation (hereafter abbreviated MT) is currently undergoing rapid development, during which less-resourced languages nevertheless seem to be less developed)—0
Système de traduction automatique statistique Anglais-Arabe—0
Systolic Arrays and Structured Pruning Co-design for Efficient Transformers in Edge Systems—0
SYSTRAN Participation to the WMT2018 Shared Task on Parallel Corpus Filtering—0
SYSTRAN Purely Neural MT Engines for WMT2017—0
SYSTRAN's Pure Neural Machine Translation Systems—0
SYSTRAN @ WMT 2021: Terminology Task—0
T\"UB\.ITAK SMT System Submission for WMT2016—0
Tackling Close Cousins: Experiences In Developing Statistical Machine Translation Systems For Marathi And Hindi—0
Tagged Back-Translation—0
Tagged Back-translation Revisited: Why Does It Really Work?—0
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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