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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 2451–2500 of 10752 papers

TitleStatusHype
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
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
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
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
"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
Evaluating Machine Translation in Cross-lingual E-Commerce Search—0
SG Translate Together - Uplifting Singapore’s translation standards with the community through technology—0
Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation—0
Adapting Large Multilingual Machine Translation Models to Unseen Low Resource Languages via Vocabulary Substitution and Neuron Selection—0
Picking Out The Best MT Model: On The Methodology Of Human EvaluationCode0
Improve MT for Search with Selected Translation Memory using Search Signals—0
Measuring the Effects of Human and Machine Translation on Website Engagement—0
Building Machine Translation System for Software Product Descriptions Using Domain-specific Sub-corpora Extraction—0
Building an Extremely Low Resource Language to High Resource Language Machine Translation System from ScratchCode0
Low Resource Chat Translation: A Benchmark for Hindi–English Language PairCode0
Filtering of Noisy Web-Crawled Parallel Corpus: the Japanese-Bulgarian Language Pair—0
Gender bias Evaluation in Luganda-English Machine Translation—0
English-Russian Data Augmentation for Neural Machine Translation—0
Language rehabilitation of people with BROCA aphasia using deep neural machine translation—0
A Neural Machine Translation Approach to Translate Text to Pictographs in a Medical Speech Translation System - The BabelDr Use Case—0
Sign Language Machine Translation and the Sign Language Lexicon: A Linguistically Informed Approach—0
You’ve translated it, now what?—0
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings—0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
DeepCon: An End-to-End Multilingual Toolkit for Automatic Minuting of Multi-Party Dialogues—0
Knowledge Distillation for Sustainable Neural Machine Translation—0
A Comparison of Data Filtering Methods for Neural Machine Translation—0
Refining an Almost Clean Translation Memory Helps Machine Translation—0
Few-Shot Regularization to Tackle Catastrophic Forgetting in Multilingual Machine Translation—0
Prefix Embeddings for In-context Machine Translation—0
Practical Attacks on Machine Translation using Paraphrase—0
Speech-to-Text and Evaluation of Multiple Machine Translation Systems—0
Current Shortcomings of Machine Translation in Spanish and Bulgarian Vis-à-vis English—0
Robust Translation of French Live Speech Transcripts—0
Improving Translation of Out Of Vocabulary Words using Bilingual Lexicon Induction in Low-Resource Machine Translation—0
All You Need is Source! A Study on Source-based Quality Estimation for Neural Machine Translation—0
Limitations and Challenges of Unsupervised Cross-lingual Pre-training—0
MultiCoNER: A Large-scale Multilingual dataset for Complex Named Entity Recognition—0
Nearest Neighbor Non-autoregressive Text Generation—0
Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks—0
MuMUR : Multilingual Multimodal Universal Retrieval—0
Discourse Cohesion Evaluation for Document-Level Neural Machine Translation—0
A Computational Interface to Translate Strategic Intent from Unstructured Language in a Low-Data SettingCode0
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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