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 10351–10400 of 10752 papers

TitleStatusHype
XLM-T: Scaling up Multilingual Machine Translation with Pretrained Cross-lingual Transformer Encoders—0
Using Spoken Word Posterior Features in Neural Machine Translation—0
Zero-Shot Paraphrase Generation with Multilingual Language Models—0
Using Syntactic Head Information in Hierarchical Phrase-Based Translation—0
Using Syntax-Based Machine Translation to Parse English into Abstract Meaning Representation—0
Using Synthetic Compounds for Word Sense Discrimination—0
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning—0
Using Term Position Similarity and Language Modeling for Bilingual Document Alignment—0
Using the Nunavut Hansard Data for Experiments in Morphological Analysis and Machine Translation—0
Using the TED Talks to Evaluate Spoken Post-editing of Machine Translation—0
Using the Textual Content of the LMF-Normalized Dictionaries for Identifying and Linking the Syntactic Behaviors to the Meanings—0
Using the Web as an Implicit Training Set: Application to Noun Compound Syntax and Semantics—0
Using Transliteration of Proper Names from Arabic to Latin Script to Improve English-Arabic Word Alignment—0
Using unlabeled dependency parsing for pre-reordering for Chinese-to-Japanese statistical machine translation—0
XMU Neural Machine Translation Online Service—0
Using Whole Document Context in Neural Machine Translation—0
XMU Neural Machine Translation Systems for WMT 17—0
Using Wikipedia to Validate the Terminology found in a Corpus of Basic Textbooks—0
Using Word Embedding for Cross-Language Plagiarism Detection—0
Using Word Embeddings for Improving Statistical Machine Translation of Phrasal Verbs—0
Using WordNet and Semantic Similarity for Bilingual Terminology Mining from Comparable Corpora—0
Using Wordnet to Improve Reordering in Hierarchical Phrase-Based Statistical Machine Translation—0
Using Word Vectors to Improve Word Alignments for Low Resource Machine Translation—0
USTCCTSU at SemEval-2024 Task 1: Reducing Anisotropy for Cross-lingual Semantic Textual Relatedness Task—0
USTED: Improving ASR with a Unified Speech and Text Encoder-Decoder—0
UTA DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports—0
UTA DLNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation—0
UTFPR at WMT 2018: Minimalistic Supervised Corpora Filtering for Machine Translation—0
Utilisation de la translitt\'eration arabe pour l'am\'elioration de l'alignement de mots \`a partir de corpus parall\`eles fran -arabe (Using Arabic Transliteration to Improve Word Alignment from French-Arabic Parallel Corpora) [in French]—0
Utilisation des fonctions de croyance pour l'estimation de param\`etres en traduction automatique (Feature calculation for Statistical Machine Translation by using belief functions) [in French]—0
Utilizing constituent structure for compound analysis—0
Utilizing Language Relatedness to improve Machine Translation: A Case Study on Languages of the Indian Subcontinent—0
CharSpan: Utilizing Lexical Similarity to Enable Zero-Shot Machine Translation for Extremely Low-resource Languages—0
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task—0
Utilizing State-of-the-art Parsers to Diagnose Problems in Treebank Annotation for a Less Resourced Language—0
Utilizing Wordnets for Cognate Detection among Indian Languages—0
Utterance-Unit Annotation for the JSL Dialogue Corpus: Toward a Multimodal Approach to Corpus Linguistics—0
UvA-MT's Participation in the WMT23 General Translation Shared Task—0
UWAV at SemEval-2017 Task 7: Automated feature-based system for locating puns—0
UWN: A Large Multilingual Lexical Knowledge Base—0
Uyghur Metaphor Detection Via Considering Emotional Consistency—0
Uzbek-English and Turkish-English Morpheme Alignment Corpora—0
UzbekTagger: The rule-based POS tagger for Uzbek language—0
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages—0
Valency and Word Order in Czech --- A Corpus Probe—0
The JHU Machine Translation Systems for WMT 2016—0
Validating Quality Estimation in a Computer-Aided Translation Workflow: Speed, Cost and Quality Trade-off—0
XMU Neural Machine Translation Systems for WAT 2017—0
VarClass: An Open-source Language Identification Tool for Language Varieties—0
Variable Bit Quantisation for LSH—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