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 8151–8200 of 10752 papers

TitleStatusHype
Privacy Issues in Online Machine Translation Services - European Perspective—0
English-to-Japanese Translation vs. Dictation vs. Post-editing: Comparing Translation Modes in a Multilingual Setting—0
Manual and Automatic Paraphrases for MT Evaluation—0
Sentiment Lexicons for Arabic Social Media—0
SubCo: A Learner Translation Corpus of Human and Machine Subtitles—0
From Interoperable Annotations towards Interoperable Resources: A Multilingual Approach to the Analysis of Discourse—0
The Denoised Web Treebank: Evaluating Dependency Parsing under Noisy Input Conditions—0
Name Translation based on Fine-grained Named Entity Recognition in a Single Language—0
CATaLog Online: Porting a Post-editing Tool to the Web—0
Syntax-based Multi-system Machine Translation—0
KantanLQR: a platform for human evaluation of machine translation output to drive engine rapid improvement—0
Extracting Structured Scholarly Information from the Machine Translation Literature—0
Creation of comparable corpora for English-Urdu, Arabic, Persian—0
Evaluating Machine Translation in a Usage Scenario—0
Parallel Sentence Extraction from Comparable Corpora with Neural Network Features—0
Building an Arabic Machine Translation Post-Edited Corpus: Guidelines and Annotation—0
iEMS – interactive experiment management system for machine translation—0
Linguistically Inspired Language Model Augmentation for MT—0
A Rule-based Shallow-transfer Machine Translation System for Scots and English—0
Paraphrasing Out-of-Vocabulary Words with Word Embeddings and Semantic Lexicons for Low Resource Statistical Machine Translation—0
QTLeap WSD/NED Corpora: Semantic Annotation of Parallel Corpora in Six Languages—0
Synset Ranking of Hindi WordNet—0
PangeaMT v 3 – customise your own machine translation environment—0
Enhancing Cross-border EU E-commerce through Machine Translation: Needed Language Resources, Challenges and Opportunities—0
Building a Corpus of Errors and Quality in Machine Translation: Experiments on Error Impact—0
Integration of machine translation paradigms—0
Amplexor MTExpert – machine translation adapted to the translation workflow—0
TweetMT: A Parallel Microblog Corpus—0
Very-large Scale Parsing and Normalization of Wiktionary Morphological Paradigms—0
The Trials and Tribulations of Predicting Post-Editing Productivity—0
Use of Domain-Specific Language Resources in Machine Translation—0
Towards producing bilingual lexica from monolingual corpora—0
Unsupervised Ranked Cross-Lingual Lexical Substitution for Low-Resource Languages—0
The Scielo Corpus: a Parallel Corpus of Scientific Publications for Biomedicine—0
Word Sense-Aware Machine Translation: Including Senses as Contextual Features for Improved Translation Models—0
Wikipedia Titles As Noun Tag Predictors—0
Uzbek-English and Turkish-English Morpheme Alignment Corpora—0
Using SMT for OCR Error Correction of Historical Texts—0
Using a Cross-Language Information Retrieval System based on OHSUMED to Evaluate the Moses and KantanMT Statistical Machine Translation Systems—0
Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation—0
Using BabelNet to Improve OOV Coverage in SMT—0
The ILMT-s2s Corpus ― A Multimodal Interlingual Map Task Corpus—0
Translation Errors and Incomprehensibility: a Case Study using Machine-Translated Second Language Proficiency Tests—0
Using Contextual Information for Machine Translation Evaluation—0
Tools and Guidelines for Principled Machine Translation Development—0
A Novel Approach to Dropped Pronoun Translation—0
Chinese Song Iambics Generation with Neural Attention-based Model—0
Dialog-based Language Learning—0
Annotation Order Matters: Recurrent Image Annotator for Arbitrary Length Image TaggingCode0
Speed-Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization—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