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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 2201–2250 of 10752 papers

TitleStatusHype
Training Mixed-Domain Translation Models via Federated Learning—0
Unifying the Convergences in Multilingual Neural Machine TranslationCode1
Teaching BERT to Wait: Balancing Accuracy and Latency for Streaming Disfluency Detection—0
The Implicit Length Bias of Label Smoothing on Beam Search Decoding—0
Jam or Cream First? Modeling Ambiguity in Neural Machine Translation with SCONES—0
Quality-Aware Decoding for Neural Machine TranslationCode1
Hausa Visual Genome: A Dataset for Multi-Modal English to Hausa Machine Translation—0
Semantically Informed Slang InterpretationCode0
ClusterFormer: Neural Clustering Attention for Efficient and Effective Transformer—0
Focus on the Target’s Vocabulary: Masked Label Smoothing for Machine TranslationCode1
Ethical Considerations for Low-resourced Machine Translation—0
DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation—0
Machine Translation for Livonian: Catering to 20 Speakers—0
BiTIIMT: A Bilingual Text-infilling Method for Interactive Machine Translation—0
Overview of the Shared Task on Machine Translation in Dravidian Languages—0
Systematic Inequalities in Language Technology Performance across the World’s LanguagesCode0
Leveraging Relaxed Equilibrium by Lazy Transition for Sequence Modeling—0
Cross-Lingual Contrastive Learning for Fine-Grained Entity Typing for Low-Resource LanguagesCode0
Automatic Generation of Distractors for Fill-in-the-Blank Exercises with Round-Trip Neural Machine Translation—0
Measuring and Mitigating Name Biases in Neural Machine Translation—0
Using Neural Machine Translation Methods for Sign Language TranslationCode1
Translation Techies @DravidianLangTech-ACL2022-Machine Translation in Dravidian Languages—0
English-Malay Cross-Lingual Embedding Alignment using Bilingual Lexicon Augmentation—0
QiuNiu: A Chinese Lyrics Generation System with Passage-Level Input—0
Prediction Difference Regularization against Perturbation for Neural Machine Translation—0
Restricted or Not: A General Training Framework for Neural Machine Translation—0
Detecting Various Types of Noise for Neural Machine Translation—0
CMU’s IWSLT 2022 Dialect Speech Translation System—0
Hierarchical Multi-task learning framework for Isometric-Speech Language TranslationCode0
Challenges and Perspectives for Innu-Aimun within Indigenous Language Technologies—0
Can We Use Word Embeddings for Enhancing Guarani-Spanish Machine Translation?Code0
English-Malay Word Embeddings Alignment for Cross-lingual Emotion Classification with Hierarchical Attention Network—0
The HW-TSC’s Offline Speech Translation System for IWSLT 2022 Evaluation—0
The HW-TSC’s Speech to Speech Translation System for IWSLT 2022 Evaluation—0
Pretrained Speech Encoders and Efficient Fine-tuning Methods for Speech Translation: UPC at IWSLT 2022Code0
NVIDIA NeMo Offline Speech Translation Systems for IWSLT 2022—0
BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine TranslationCode0
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out TrainingCode0
JHU IWSLT 2022 Dialect Speech Translation System Description—0
Prompt-Driven Neural Machine TranslationCode1
Bias Mitigation in Machine Translation Quality EstimationCode0
Human evaluation of web-crawled parallel corpora for machine translation—0
The NiuTrans’s Submission to the IWSLT22 English-to-Chinese Offline Speech Translation Task—0
Why don’t people use character-level machine translation?—0
Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine TranslationCode1
Synchronous Refinement for Neural Machine Translation—0
Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine TranslationCode0
Producing Standard German Subtitles for Swiss German TV Content—0
Improving Machine Translation Formality Control with Weakly-Labelled Data Augmentation and Post Editing Strategies—0
Neural Machine Translation for Fact-checking Temporal Claims—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