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 7951–8000 of 10752 papers

TitleStatusHype
Using Interlinear Glosses as Pivot in Low-Resource Multilingual Machine Translation—0
Low-Resource Machine Translation Using Cross-Lingual Language Model Pretraining—0
Low-resource Machine Translation: what for? who for? An observational study on a dedicated Tetun language translation service—0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages—0
Low Resource Multimodal Neural Machine Translation of English-Hindi in News Domain—0
Low-resource Neural Machine Translation: Benchmarking State-of-the-art Transformer for Wolof<->French—0
Low-Resource Neural Machine Translation for Southern African Languages—0
Low-Resource Semantic Role Labeling—0
Low Resource Similar Language Neural Machine Translation for Tamil-Telugu—0
Low-Resource Speech-to-Text Translation—0
Low-Resource Translation as Language Modeling—0
LR Parsing for LCFRS—0
LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics—0
LSTM Neural Reordering Feature for Statistical Machine Translation—0
LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better—0
LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover’s Distance—0
LTRC-MT Simple \& Effective Hindi-English Neural Machine Translation Systems at WAT 2019—0
Lump at SemEval-2017 Task 1: Towards an Interlingua Semantic Similarity—0
LV-CTC: Non-autoregressive ASR with CTC and latent variable models—0
LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation—0
LZ1904 at SemEval-2021 Task 5: Bi-LSTM-CRF for Toxic Span Detection using Pretrained Word Embedding—0
M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention—0
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt—0
M3ST: Mix at Three Levels for Speech Translation—0
Maastricht University’s Large-Scale Multilingual Machine Translation System for WMT 2021—0
Machine Learning Approaches for Amharic Parts-of-speech Tagging—0
Machine Learning for Hybrid Machine Translation—0
Machine Learning Testing: Survey, Landscapes and Horizons—0
Machine-oriented NMT Adaptation for Zero-shot NLP tasks: Comparing the Usefulness of Close and Distant Languages—0
Machine Translation Acceptance Among Professional Linguists: Are We Nearing the Tipping Point?—0
Machine Translation Advancements of Low-Resource Indian Languages by Transfer Learning—0
Machine Translation Aided Bilingual Data-to-Text Generation and Semantic Parsing—0
Machine Translation: A Literature Review—0
Machine Translation and Automated Analysis of the Sumerian Language—0
Machine Translation and Monolingual Postediting: The AFRL WMT-14 System—0
Machine Translation Approaches and Survey for Indian Languages—0
Machine Translation Approaches and Survey for Indian Languages—0
Machine Translation as an Academic Writing Aid for Medical Practitioners—0
Machine Translation at Booking.com: Journey and Lessons Learned—0
Machine translation at Booking.com: what's next?—0
Machine Translation Between High-resource Languages in a Language Documentation Setting—0
Machine Translation between Vietnamese and English: an Empirical Study—0
Machine Translation by Modeling Predicate-Argument Structure Transformation—0
Machine Translation by Projecting Text into the Same Phonetic-Orthographic Space Using a Common Encoding—0
Machine translation considering context information using Encoder-Decoder model—0
Machine Translation Customization via Automatic Training Data Selection from the Web—0
Machine Translation Decoding beyond Beam Search—0
Machine Translation Detection from Monolingual Web-Text—0
Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation—0
Machine Translation Evaluation Benchmark for Wu Chinese: Workflow and Analysis—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