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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 4051–4100 of 10752 papers

TitleStatusHype
Zero-shot translation among Indian languages—0
Punjabi to English Bidirectional NMT System—0
PhraseOut: A Code Mixed Data Augmentation Method for MultilingualNeural Machine Tranlsation—0
The UPC RDF-to-Text System at WebNLG Challenge 2020—0
Train Once, and Decode As You Like—0
Revitalization of Indigenous Languages through Pre-processing and Neural Machine Translation: The case of Inuktitut—0
A Multilingual Reading Comprehension System for more than 100 Languages—0
Coreference Strategies in English-German Translation—0
A Test Suite for Evaluating Discourse Phenomena in Document-level Neural Machine Translation—0
Unifying Input and Output Smoothing in Neural Machine Translation—0
The ADAPT Centre’s Participation in WAT 2020 English-to-Odia Translation Task—0
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation—0
Predicting and Using Target Length in Neural Machine Translation—0
Vietnamese-English Translation with Transformer and Back Translation in VLSP 2020 Machine Translation Shared Task—0
Context-Aware Text Normalisation for Historical Dialects—0
Incorporating Noisy Length Constraints into Transformer with Length-aware Positional Encodings—0
Translation vs. Dialogue: A Comparative Analysis of Sequence-to-Sequence Modeling—0
Sparse Transcription—0
Neural Machine Translation Models with Back-Translation for the Extremely Low-Resource Indigenous Language BribriCode0
Multimodal Neural Machine Translation for English to Hindi—0
Informative Manual Evaluation of Machine Translation OutputCode0
Component Sharing in English and Chinese Clause Complex—0
Comparison of the effects of attention mechanism on translation tasks of different lengths of ambiguous words—0
Punjabi to Urdu Machine Translation System—0
Voice@SRIB at SemEval-2020 Tasks 9 and 12: Stacked Ensemblingmethod for Sentiment and Offensiveness detection in Social Media—0
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation—0
Machine Translation of Novels in the Age of TransformerCode0
A Comprehensive Review on Recent Methods and Challenges of Video Description—0
Using Multiple Subwords to Improve English-Esperanto Automated Literary Translation Quality—0
Unsupervised Word Translation Pairing using Refinement based Point Set Registration—0
Decoding and Diversity in Machine Translation—0
A Panoramic Survey of Natural Language Processing in the Arab World—0
Two-Way Neural Machine Translation: A Proof of Concept for Bidirectional Translation Modeling using a Two-Dimensional Grid—0
Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural NetworksCode0
Findings of the 2020 Conference on Machine Translation (WMT20)—0
Master Thesis: Neural Sign Language Translation by Learning Tokenization—0
iPerceive: Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering—0
A Hybrid Approach for Improved Low Resource Neural Machine Translation using Monolingual Data—0
Language Models not just for Pre-training: Fast Online Neural Noisy Channel ModelingCode0
Inference-only sub-character decomposition improves translation of unseen logographic characters—0
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization—0
Incorporating a Local Translation Mechanism into Non-autoregressive TranslationCode0
How to Measure Gender Bias in Machine Translation: Optimal Translators, Multiple Reference Points—0
From Unsupervised Machine Translation To Adversarial Text Generation—0
Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara—0
Simultaneous Speech-to-Speech Translation System with Neural Incremental ASR, MT, and TTS—0
BERT-JAM: Boosting BERT-Enhanced Neural Machine Translation with Joint Attention—0
Neural Architecture Search with an Efficient Multiobjective Evolutionary Framework—0
Template Controllable keywords-to-text Generation—0
AlphaMWE: Construction of Multilingual Parallel Corpora with MWE AnnotationsCode0
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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