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 2901–2950 of 10752 papers

TitleStatusHype
Benchmarking Data-driven Automatic Text Simplification for German—0
Discontinuous Statistical Machine Translation with Target-Side Dependency Syntax—0
Discontinuous Verb Phrases in Parsing and Machine Translation of English and German—0
Creating Interactive Macaronic Interfaces for Language Learning—0
Domain Adaptation and Attention-Based Unknown Word Replacement in Chinese-to-Japanese Neural Machine Translation—0
Discourse Analysis and Its Applications—0
Discourse and Document-level Information for Evaluating Language Output Tasks—0
Discourse Annotation in the PDTB: The Next Generation—0
Discourse Annotation of Non-native Spontaneous Spoken Responses Using the Rhetorical Structure Theory Framework—0
Discourse-aware Statistical Machine Translation as a Context-sensitive Spell Checker—0
Creating Domain-Specific Translation Memories for Machine Translation Fine-tuning: The TRENCARD Bilingual Cardiology Corpus—0
Discourse Cohesion Evaluation for Document-Level Neural Machine Translation—0
Attention Link: An Efficient Attention-Based Low Resource Machine Translation Architecture—0
Discourse-level Annotation over Europarl for Machine Translation: Connectives and Pronouns—0
Discourse-Related Language Contrasts in English-Croatian Human and Machine Translation—0
Discourse Representation Structure Parsing with Recurrent Neural Networks and the Transformer Model—0
A Neural Network Model for Low-Resource Universal Dependency Parsing—0
Discourse Structure and Computation: Past, Present and Future—0
Discourse Structure in Machine Translation Evaluation—0
Discovering Bilingual Lexicons in Polyglot Word Embeddings—0
Discovering Light Verb Constructions and their Translations from Parallel Corpora without Word Alignment—0
Analysing ParCor and its Translations by State-of-the-art SMT Systems—0
Discovering Non-Monotonic Autoregressive Ordering for Text Generation Models using Sinkhorn Distributions—0
Discovering Parallel Language Resources for Training MT Engines—0
Discovering Potential Terminological Relationships from Twitter's Timed Content—0
Discovery of Discourse-Related Language Contrasts through Alignment Discrepancies in English-German Translation—0
DiscreTalk: Text-to-Speech as a Machine Translation Problem—0
Bengali to Assamese Statistical Machine Translation using Moses (Corpus Based)—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
Discrete Structural Planning for Generating Diverse Translations—0
Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey—0
Discrete Structural Planning for Neural Machine Translation—0
Creating Arabic LLM Prompts at Scale—0
Discriminating between Similar Languages Using a Combination of Typed and Untyped Character N-grams and Words—0
Analysing Lexical Consistency in Translation—0
Creating and using large monolingual parallel corpora for sentential paraphrase generation—0
Discriminative Joint Modeling of Lexical Variation and Acoustic Confusion for Automated Narrative Retelling Assessment—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
Discriminative Learning with Natural Annotations: Word Segmentation as a Case Study—0
Discriminative Preordering Meets Kendall's Maximization—0
Creating a massively parallel Bible corpus—0
Discriminative Reranking for Neural Machine Translation—0
Discriminative statistical approaches for multilingual speech understanding (Approches statistiques discriminantes pour l'interpr\'etation s\'emantique multilingue de la parole) [in French]—0
Discriminative Training of 150 Million Translation Parameters and Its Application to Pruning—0
Disentangled Mask Attention in Transformer—0
BERTTune: Fine-Tuning Neural Machine Translation with BERTScore—0
Disentangled Sequence to Sequence Learning for Compositional Generalization—0
Disentangling Singlish Discourse Particles with Task-Driven Representation—0
Disentangling the Roles of Target-Side Transfer and Regularization in Multilingual Machine Translation—0
Attention for Implicit Discourse Relation Recognition—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