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 6651–6700 of 10752 papers

TitleStatusHype
German-Arabic Speech-to-Speech Translation for Psychiatric Diagnosis—0
German Compounds and Statistical Machine Translation. Can they get along?—0
German Dialect Identification in Interview Transcriptions—0
Getting Gender Right in Neural Machine Translation—0
GF Wide-coverage English-Finnish MT system for WMT 2015—0
GHKM Rule Extraction and Scope-3 Parsing in Moses—0
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes—0
Global Intelligent Content: Active Curation of Language Resources using Linked Data—0
Global Pre-ordering for Improving Sublanguage Translation—0
Glossary functionality in commercial machine translation: does it help? A first step to identify best practices for a language service provider—0
Going beyond sentences when applying tree kernels—0
Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation—0
Goku’s Participation in WAT 2020—0
Good, but not always Fair: An Evaluation of Gender Bias for three commercial Machine Translation Systems—0
Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation—0
Good for Misconceived Reasons: Revisiting Neural Multimodal Machine Translation—0
GOSt-MT: A Knowledge Graph for Occupation-related Gender Biases in Machine Translation—0
GoURMET – Machine Translation for Low-Resourced Languages—0
Gradable ChatGPT Translation Evaluation—0
GradAscent at EmoInt-2017: Character and Word Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection—0
Gradient-guided Loss Masking for Neural Machine Translation—0
Grading Conversational Responses Of Chatbots—0
GRAFIX: Automated Rule-Based Post Editing System to Improve English-Persian SMT Output—0
GRAFT: A Graph-based Flow-aware Agentic Framework for Document-level Machine Translation—0
GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning—0
Grammar Accuracy Evaluation (GAE): Quantifiable Quantitative Evaluation of Machine Translation Models—0
Grammar-Based Concept Alignment for Domain-Specific Machine Translation—0
Grammar Error Correction Using Pseudo-Error Sentences and Domain Adaptation—0
Grammar rules for the isiZulu complex verb—0
Grammatical Error Correction: A Survey of the State of the Art—0
Grammatical Error Correction Considering Multi-word Expressions—0
Grammatical Error Correction for Low-Resource Languages: The Case of Zarma—0
Grammatical Error Correction: Machine Translation and Classifiers—0
Grammatical error correction using hybrid systems and type filtering—0
Grammatical error correction using neural machine translation—0
Grammatical Error Generation Based on Translated Fragments—0
Graph Algebraic Combinatory Categorial Grammar—0
Graph-based alignment of narratives for automated neurological assessment—0
Graph-Based Collective Lexical Selection for Statistical Machine Translation—0
Graph-based Dependency Parsing with Bidirectional LSTM—0
Graph-based Semi-Supervised Learning of Translation Models from Monolingual Data—0
Graph-based Semi-Supervised Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging—0
Graph-Based Translation Via Graph Segmentation—0
Graph-Based Unsupervised Learning of Word Similarities Using Heterogeneous Feature Types—0
Graph-Based Word Alignment for Clinical Language Evaluation—0
Graph Convolutional Encoders for Syntax-aware Neural Machine Translation—0
Graph Convolutional Network with Sequential Attention For Goal-Oriented Dialogue Systems—0
Graph Databases for Designing High-Performance Speech Recognition Grammars—0
Graph Neural Networks for Multiparallel Word Alignment—0
Graph Neural Networks for Multiparallel Word Alignment—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