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 6801–6850 of 10752 papers

TitleStatusHype
Improving Japanese-to-English Neural Machine Translation by Paraphrasing the Target Language—0
Improving Japanese-to-English Neural Machine Translation by Voice Prediction—0
SMT reranked NMT—0
Keyword-based Query Comprehending via Multiple Optimized-Demand Augmentation—0
Key-value Attention Mechanism for Neural Machine Translation—0
Improving Low-Resource Neural Machine Translation with Filtered Pseudo-Parallel CorpusCode0
Selective Decoding for Cross-lingual Open Information Extraction—0
Semantics-Enhanced Task-Oriented Dialogue Translation: A Case Study on Hotel Booking—0
MultiNews: A Web collection of an Aligned Multimodal and Multilingual Corpus—0
Controlling Target Features in Neural Machine Translation via Prefix Constraints—0
Improving Neural Machine Translation through Phrase-based Forced Decoding—0
Between Reading Time and Information Structure—0
Improving Neural Text Normalization with Data Augmentation at Character- and Morphological Levels—0
Building a Better Bitext for Structurally Different Languages through Self-training—0
Extracting a Lexicon of Discourse Connectives in Czech from an Annotated Corpus—0
Context-Aware Smoothing for Neural Machine Translation—0
An Empirical Study of Language Relatedness for Transfer Learning in Neural Machine Translation—0
Automatically Extracting Variant-Normalization Pairs for Japanese Text Normalization—0
Concept Equalization to Guide Correct Training of Neural Machine Translation—0
Investigating Phrase-Based and Neural-Based Machine Translation on Low-Resource Settings—0
Comparison of SMT and NMT trained with large Patent Corpora: Japio at WAT2017—0
Reference-based Metrics can be Replaced with Reference-less Metrics in Evaluating Grammatical Error Correction Systems—0
Comparing Recurrent and Convolutional Architectures for English-Hindi Neural Machine Translation—0
Japanese to English/Chinese/Korean Datasets for Translation Quality Estimation and Automatic Post-Editing—0
CADET: Computer Assisted Discovery Extraction and Translation—0
A Parallel Recurrent Neural Network for Language Modeling with POS Tags—0
Overview of the 4th Workshop on Asian Translation—0
CKY-based Convolutional Attention for Neural Machine Translation—0
Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification—0
Learning How to Simplify From Explicit Labeling of Complex-Simplified Text PairsCode0
Recall is the Proper Evaluation Metric for Word Segmentation—0
Deriving Consensus for Multi-Parallel Corpora: an English Bible StudyCode0
Neural Machine Translation: Basics, Practical Aspects and Recent Trends—0
Patent NMT integrated with Large Vocabulary Phrase Translation by SMT at WAT 2017—0
Attentive Language Models—0
XMU Neural Machine Translation Online Service—0
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder—0
XMU Neural Machine Translation Systems for WAT 2017—0
Tokyo Metropolitan University Neural Machine Translation System for WAT 2017—0
Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification—0
Unsupervised Bilingual Segmentation using MDL for Machine Translation—0
Unsupervised Machine Translation Using Monolingual Corpora OnlyCode0
Generating Natural Adversarial ExamplesCode0
Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss GermanCode0
Unsupervised Neural Machine TranslationCode0
Evaluation of Automatic Video Captioning Using Direct Assessment—0
JESC: Japanese-English Subtitle Corpus—0
A Dual Encoder Sequence to Sequence Model for Open-Domain Dialogue ModelingCode0
Attention-Based Models for Text-Dependent Speaker VerificationCode0
Rotational Unit of MemoryCode0
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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