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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 1851–1900 of 10752 papers

TitleStatusHype
Semantically Consistent Data Augmentation for Neural Machine Translation via Conditional Masked Language ModelCode0
Mega: Moving Average Equipped Gated AttentionCode2
PePe: Personalized Post-editing Model utilizing User-generated Post-edits—0
LINGUIST: Language Model Instruction Tuning to Generate Annotated Utterances for Intent Classification and Slot Tagging—0
EffEval: A Comprehensive Evaluation of Efficiency for MT Evaluation MetricsCode0
Relaxed Attention for Transformer Models—0
Vega-MT: The JD Explore Academy Translation System for WMT22Code1
The first neural machine translation system for the Erzya languageCode1
Learning Decoupled Retrieval Representation for Nearest Neighbour Neural Machine Translation—0
A Snapshot into the Possibility of Video Game Machine Translation—0
Transformer-based Detection of Multiword Expressions in Flower and Plant Names—0
An Empirical Study of Automatic Post-Editing—0
Rethinking Round-Trip Translation for Machine Translation EvaluationCode0
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It—0
Toward Improving Health Literacy in Patient Education Materials with Neural Machine Translation Models—0
Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican—0
Revisiting Neural Scaling Laws in Language and Vision—0
Rethink about the Word-level Quality Estimation for Machine Translation from Human JudgementCode0
Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence Models—0
MaxMatch-Dropout: Subword Regularization for WordPieceCode1
Adapting to Non-Centered Languages for Zero-shot Multilingual TranslationCode0
Knowledge Based Template Machine Translation In Low-Resource Setting—0
Leveraging machine translation for cross-lingual fine-grained cyberbullying classification amongst pre-adolescentsCode0
Adam Mickiewicz University at WMT 2022: NER-Assisted and Quality-Aware Neural Machine Translation—0
Facilitating Global Team Meetings Between Language-Based Subgroups: When and How Can Machine Translation Help?—0
That Slepen Al the Nyght with Open Ye! Cross-era Sequence Segmentation with Switch-memory—0
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine TranslationCode0
"Es geht um Respekt, nicht um Technologie": Erkenntnisse aus einem Interessensgruppen-übergreifenden Workshop zu genderfairer Sprache und Sprachtechnologie—0
Rare but Severe Neural Machine Translation Errors Induced by Minimal Deletion: An Empirical Study on Chinese and EnglishCode0
Informative Language Representation Learning for Massively Multilingual Neural Machine TranslationCode1
Filtering of Noisy Web-Crawled Parallel Corpus: the Japanese-Bulgarian Language Pair—0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
Language rehabilitation of people with BROCA aphasia using deep neural machine translation—0
DeepCon: An End-to-End Multilingual Toolkit for Automatic Minuting of Multi-Party Dialogues—0
Adapting Large Multilingual Machine Translation Models to Unseen Low Resource Languages via Vocabulary Substitution and Neuron Selection—0
Gender bias Evaluation in Luganda-English Machine Translation—0
Refining an Almost Clean Translation Memory Helps Machine Translation—0
Picking Out The Best MT Model: On The Methodology Of Human EvaluationCode0
Evaluating Machine Translation in Cross-lingual E-Commerce Search—0
Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation—0
Building Machine Translation System for Software Product Descriptions Using Domain-specific Sub-corpora Extraction—0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings—0
Measuring the Effects of Human and Machine Translation on Website Engagement—0
SG Translate Together - Uplifting Singapore’s translation standards with the community through technology—0
Robust Translation of French Live Speech Transcripts—0
Prefix Embeddings for In-context Machine Translation—0
Speech-to-Text and Evaluation of Multiple Machine Translation Systems—0
Few-Shot Regularization to Tackle Catastrophic Forgetting in Multilingual Machine Translation—0
A Neural Machine Translation Approach to Translate Text to Pictographs in a Medical Speech Translation System - The BabelDr Use Case—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