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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 3151–3200 of 10752 papers

TitleStatusHype
Dynamic Language Models for Streaming Text—0
Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement—0
Dynamic Masking for Improved Stability in Spoken Language Translation—0
Bilingual Word Embeddings with Bucketed CNN for Parallel Sentence Extraction—0
Dynamic Oracle for Neural Machine Translation in Decoding Phase—0
Bilingual Word Representations with Monolingual Quality in Mind—0
Dynamic Position Encoding for Transformers—0
Attention-Driven Body Pose Encoding for Human Activity Recognition—0
Dynamic Scheduled Sampling with Imitation Loss for Neural Text Generation—0
Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation—0
Dynamic Terminology Integration for COVID-19 and other Emerging Domains—0
Dynamic Terminology Integration Methods in Statistical Machine Translation—0
An Aligned French-Chinese corpus of 10K segments from university educational material—0
Dynamic Topic Adaptation for SMT using Distributional Profiles—0
Enhancing AI-based Generation of Software Exploits with Contextual Information—0
Encoding Gated Translation Memory into Neural Machine Translation—0
E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language—0
Bingo at IJCNLP-2017 Task 4: Augmenting Data using Machine Translation for Cross-linguistic Customer Feedback Classification—0
EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation—0
BIOS: An Algorithmically Generated Biomedical Knowledge Graph—0
Annotated Corpora for Word Alignment between Japanese and English and its Evaluation with MAP-based Word Aligner—0
EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation—0
Encouraging Consistent Translation Choices—0
Echo State Neural Machine Translation—0
ECNU at SemEval-2016 Task 1: Leveraging Word Embedding From Macro and Micro Views to Boost Performance for Semantic Textual Similarity—0
ECNU at SemEval-2017 Task 1: Leverage Kernel-based Traditional NLP features and Neural Networks to Build a Universal Model for Multilingual and Cross-lingual Semantic Textual Similarity—0
ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection—0
ECNUCS: Measuring Short Text Semantic Equivalence Using Multiple Similarity Measurements—0
End-to-End Lexically Constrained Machine Translation for Morphologically Rich Languages—0
ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation—0
ECNU: Leveraging Word Embeddings to Boost Performance for Paraphrase in Twitter—0
Eco.pangeamt: Industrializing Neural MT—0
Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training—0
EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation—0
Bi-Text Alignment of Movie Subtitles for Spoken English-Arabic Statistical Machine Translation—0
Edinburgh’s End-to-End Multilingual Speech Translation System for IWSLT 2021—0
Edinburgh's Machine Translation Systems for European Language Pairs—0
Edinburgh's Phrase-based Machine Translation Systems for WMT-14—0
Edinburgh's Statistical Machine Translation Systems for WMT16—0
Edinburgh's Submissions to the 2020 Machine Translation Efficiency Task—0
Edinburgh's Syntax-Based Machine Translation Systems—0
Edinburgh's Syntax-Based Systems at WMT 2014—0
Edinburgh's Syntax-Based Systems at WMT 2015—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
End-to-End Speech Translation of Arabic to English Broadcast News—0
Edit Distance: A New Data Selection Criterion for Domain Adaptation in SMT—0
Edit Distance Based Curriculum Learning for Paraphrase Generation—0
Black-box Adversarial Sample Generation Based on Differential Evolution—0
Coverage Embedding Models for Neural Machine Translation—0
Attention Calibration for Transformer in 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
5AdminBLEU score43.8—Unverified
6Transformer (ADMIN init)BLEU 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