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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 5751–5800 of 10752 papers

TitleStatusHype
NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task—0
NICT’s Neural Machine Translation Systems for the WAT21 Restricted Translation Task—0
NICT‘s Submission To WAT 2020: How Effective Are Simple Many-To-Many Neural Machine Translation Models?—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 News Translation Task—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 Translation Robustness Task—0
NICT's Unsupervised Neural and Statistical Machine Translation Systems for the WMT19 News Translation Task—0
NITK-UoH: Tamil-Telugu Machine Translation Systems for the WMT21 Similar Language Translation Task—0
NIT Rourkela Machine Translation(MT) System Submission to WAT 2022 for MultiIndicMT: An Indic Language Multilingual Shared Task—0
NITS-VC System for VATEX Video Captioning Challenge 2020—0
NLP and Online Health Reports: What do we say and what do we mean?—0
NLP-enabled Trajectory Map-matching in Urban Road Networks using a Transformer-based Encoder-decoder—0
NLPRL at WAT2019: Transformer-based Tamil -- English Indic Task Neural Machine Translation System—0
NLPRL Odia-English: Indic Language Neural Machine Translation System—0
NLPRL System for Very Low Resource Supervised Machine Translation—0
nmT5 -- Is parallel data still relevant for pre-training massively multilingual language models?—0
nmT5 - Is parallel data still relevant for pre-training massively multilingual language models?—0
NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations—0
NMT based Similar Language Translation for Hindi - Marathi—0
NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning—0
NMT or SMT: Case Study of a Narrow-domain English-Latvian Post-editing Project—0
NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems—0
NoahNMT at WMT 2021: Dual Transfer for Very Low Resource Supervised Machine Translation—0
NoDeeLe: A Novel Deep Learning Schema for Evaluating Neural Machine Translation Systems—0
Noise-robust Cross-modal Interactive Learning with Text2Image Mask for Multi-modal Neural Machine Translation—0
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction—0
Noisy-parallel and comparable corpora filtering methodology for the extraction of bi-lingual equivalent data at sentence level—0
Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model—0
Noisy Parallel Corpus Filtering through Projected Word Embeddings—0
No more beating about the bush : A Step towards Idiom Handling for Indian Language NLP—0
Non-Autoregressive Image Captioning with Counterfactuals-Critical Multi-Agent Learning—0
Non-Autoregressive Machine Translation: It's Not as Fast as it Seems—0
Non-Autoregressive Machine Translation: It’s Not as Fast as it Seems—0
Non-Autoregressive Machine Translation: It's Not as Fast as it Seems—0
Non-Autoregressive Machine Translation with Auxiliary Regularization—0
Non-Autoregressive Models are Better Multilingual Translators—0
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input—0
Non-Autoregressive Neural Machine Translation with Consistency Regularization Optimized Variational Framework—0
Non-Autoregressive Neural Machine Translation: A Call for Clarity—0
Non-Autoregressive Neural Machine Translation with Consistency Regularization Optimized Variational Framework—0
Listen and Fill in the Missing Letters: Non-Autoregressive Transformer for Speech Recognition—0
Non-autoregressive Transformer by Position Learning—0
Non-Euclidean Hierarchical Representational Learning using Hyperbolic Graph Neural Networks for Environmental Claim Detection—0
Non-linear Learning for Statistical Machine Translation—0
Non-Linear Models for Confidence Estimation—0
Non-linear recursive grammar for Sign languages (Grammaire r\'ecursive non lin\'eaire pour les langues des signes) [in French]—0
Non-Monotonic Attention-based Read/Write Policy Learning for Simultaneous Translation—0
Non-Monotonic Sentence Alignment via Semisupervised Learning—0
Non-Parametric Adaptation for Neural Machine Translation—0
Nonparametric Bayesian Semi-supervised Word Segmentation—0
Non-parametric, Nearest-neighbor-assisted Fine-tuning for Neural Machine Translation—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