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 5251–5300 of 10752 papers

TitleStatusHype
Richer Interpolative Smoothing Based on Modified Kneser-Ney Language Modeling—0
Rich Morphology Generation Using Statistical Machine Translation—0
Riemannian Stochastic Gradient Descent for Tensor-Train Recurrent Neural Networks—0
Right-truncatable Neural Word Embeddings—0
Risam\'alheild: A Very Large Icelandic Text Corpus—0
RIVAL: Reinforcement Learning with Iterative and Adversarial Optimization for Machine Translation—0
RMBR: A Regularized Minimum Bayes Risk Reranking Framework for Machine Translation—0
RMHIDD: A Reddit Mental Health Intervention Dialogue Dataset—0
Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models—0
Robust Fragment-Based Framework for Cross-lingual Sentence Retrieval—0
Robust Machine Translation with Domain Sensitive Pseudo-Sources: Baidu-OSU WMT19 MT Robustness Shared Task System Report—0
Robustness of Multi-Source MT to Transcription Errors—0
Robust Neural Machine Translation for Clean and Noisy Speech Transcripts—0
Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation—0
Robust Neural Machine Translation with ASR Errors—0
Robust Neural Machine Translation with Doubly Adversarial Inputs—0
Robust Neural Machine Translation with Joint Textual and Phonetic Embedding—0
Robust parfda Statistical Machine Translation Results—0
Robust Part-of-speech Tagging of Arabic Text—0
Robust Subgraph Generation Improves Abstract Meaning Representation Parsing—0
Robust Text Classification using Sub-Word Information in Input Word Representations.—0
Robust Translation of French Live Speech Transcripts—0
Robust Transliteration Mining from Comparable Corpora with Bilingual Topic Models—0
Robust Tuning Datasets for Statistical Machine Translation—0
Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training—0
Role of Morphology Injection in Statistical Machine Translation—0
Romanian TimeBank: An Annotated Parallel Corpus for Temporal Information—0
Romanized Arabic Transliteration—0
融合零指代识别的篇章级机器翻译(Context-aware Machine Translation Integrating Zero Pronoun Recognition)—0
融合XLM词语表示的神经机器译文自动评价方法(Neural Automatic Evaluation of Machine Translation Method Combined with XLM Word Representation)—0
融入音素特征的英-泰-老多语言神经机器翻译方法(English-Thai-Lao multilingual neural machine translation fused with phonemic features)—0
Round trips with meaning stopovers—0
RTM at SemEval-2017 Task 1: Referential Translation Machines for Predicting Semantic Similarity—0
RTM-DCU: Predicting Semantic Similarity with Referential Translation Machines—0
RTM results for Predicting Translation Performance—0
RTM Stacking Results for Machine Translation Performance Prediction—0
Rule-based Machine Translation between Indonesian and Malaysian—0
Rule-based Machine translation from English to Finnish—0
Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladin—0
Rule-Based Pronominal Anaphora Treatment for Machine Translation—0
Rule-based Reordering and Post-Processing for Indonesian-Korean Statistical Machine Translation—0
Rule-based Reordering Space in Statistical Machine Translation—0
Rule-based Syntactic Preprocessing for Syntax-based Machine Translation—0
Rule-Based Translation of Spanish Verb-Noun Combinations into Basque—0
Rule Based Transliteration Scheme for English to Punjabi—0
Rule Extraction for Tree-to-Tree Transducers by Cost Minimization—0
Rule Selection with Soft Syntactic Features for String-to-Tree Statistical Machine Translation—0
Russian-Chinese Sentence-level Aligned News Corpus—0
Russian-English Bidirectional Machine Translation System—0
Russian Stress Prediction using Maximum Entropy Ranking—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