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 3551–3600 of 10752 papers

TitleStatusHype
Using Machine Translation to Localize Task Oriented NLG Output—0
A Survey on Low-Resource Neural Machine Translation—0
Using CollGram to Compare Formulaic Language in Human and Neural Machine Translation—0
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
IITP at WAT 2021: System description for English-Hindi Multimodal Translation Task—0
Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN—0
MultiTraiNMT: Training Materials to Approach Neural Machine Translation from Scratch—0
Using CollGram to Compare Formulaic Language in Human and Machine Translation—0
Knowledge Distillation for Quality EstimationCode0
Building a Corpus for Corporate Websites Machine Translation Evaluation. A Step by Step Methodological Approach—0
Interactive Models for Post-Editing—0
NoDeeLe: A Novel Deep Learning Schema for Evaluating Neural Machine Translation Systems—0
Integration of Machine Translation and Translation Memory: Post-Editing Efforts—0
The changing profile of the translator profession at the European Central Bank—0
The Post-Editing Workflow: Training Challenges for LSPs, Post-Editors and Academia—0
Zero-pronoun Data Augmentation for Japanese-to-English Translation—0
Machine Translation Literacy Instruction for Non-Translators: A Comparison of Five Delivery Formats—0
Cross-Lingual Named Entity Recognition via FastAlign: a Case Study—0
Audiovisual Translation through NMT and Subtitling in the Netflix Series ‘Cable Girls’—0
On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation—0
IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task—0
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text GenerationCode0
Neural Machine Translation for Low-Resource Languages: A Survey—0
Digging Errors in NMT: Evaluating and Understanding Model Errors from Partial Hypothesis Space—0
Traditional Machine Learning and Deep Learning Models for Argumentation Mining in Russian Texts—0
On a novel training algorithm for sequence-to-sequence predictive recurrent networks—0
Power Law Graph Transformer for Machine Translation and Representation LearningCode0
Building Intelligent Autonomous Navigation Agents—0
Language Models are Good Translators—0
DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual EncodersCode0
On the Influence of Machine Translation on Language Origin Obfuscation—0
End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages—0
Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training—0
Phrase-level Active Learning for Neural Machine Translation—0
Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study—0
Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation—0
Central Kurdish machine translation: First large scale parallel corpus and experiments—0
Lost in Interpreting: Speech Translation from Source or Interpreter?—0
Evaluating Gender Bias in Hindi-English Machine Translation—0
Alternated Training with Synthetic and Authentic Data for Neural Machine Translation—0
Code to Comment Translation: A Comparative Study on Model Effectiveness & ErrorsCode0
Language Tags Matter for Zero-Shot Neural Machine Translation—0
English to Bangla Machine Translation Using Recurrent Neural Network—0
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep LearningCode0
Guiding Teacher Forcing with Seer Forcing for Neural Machine Translation—0
Don't Rule Out Monolingual Speakers: A Method For Crowdsourcing Machine Translation Data—0
Predicting the Ordering of Characters in Japanese Historical Documents—0
Machine Translation into Low-resource Language Varieties—0
Towards User-Driven Neural Machine TranslationCode0
Semi-Supervised and Unsupervised Sense Annotation via Translations—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