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 2551–2600 of 10752 papers

TitleStatusHype
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation—0
Dangerous Relations in Dependency Treebanks—0
DanProof: Pedagogical Spell and Grammar Checking for Danish—0
DAQE: Exploring the Direct Assessment on Word-Level Quality Estimation in Machine Translation—0
Cross-Attention Based Influence Model for Manual and Nonmanual Sign Language Analysis—0
Dashboard: A Tool for Integration, Validation, and Visualization of Distributed NLP Systems on Heterogeneous Platforms—0
Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican—0
Data-adaptive Transfer Learning for Low-resource Translation: A Case Study in Haitian—0
Attention Strategies for Multi-Source Sequence-to-Sequence Learning—0
Data Augmentation and Terminology Integration for Domain-Specific Sinhala-English-Tamil Statistical Machine Translation—0
Data Augmentation by Concatenation for Low-Resource Translation: A Mystery and a Solution—0
Data Augmentation for End-to-End Speech Translation: FBK@IWSLT ‘19—0
Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings—0
Analysing the Effect of Out-of-Domain Data on SMT Systems—0
Automatic Construction of a MultiWord Expressions Bilingual Lexicon: A Statistical Machine Translation Evaluation Perspective—0
Data Augmentation for Neural Machine Translation using Generative Language Model—0
Data Augmentation for Sign Language Gloss Translation—0
Data Augmentation Techniques for Machine Translation of Code-Switched Texts: A Comparative Study—0
Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation—0
Data augmentation using back-translation for context-aware neural machine translation—0
Data Augmentation using Machine Translation for Fake News Detection in the Urdu Language—0
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda—0
Data-dependent Gaussian Prior Objective for Language Generation—0
Critical Learning Periods: Leveraging Early Training Dynamics for Efficient Data Pruning—0
Data-Driven Adaptive Simultaneous Machine Translation—0
Data-Driven Adaptive Simultaneous Machine Translation—0
Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation—0
Data-driven learning of symbolic constraints for a log-linear model in a phonological setting—0
Data-driven sentence generation with non-isomorphic trees—0
Data-Driven Text Simplification—0
Data Efficient Direct Speech-to-Text Translation with Modality Agnostic Meta-Learning—0
Data enhancement and selection strategies for the word-level Quality Estimation—0
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection—0
Data Filtering using Cross-Lingual Word Embeddings—0
Automatic Detection of Machine Translated Text and Translation Quality Estimation—0
Data Issues of the Multilingual Translation Matrix—0
Automatic Detection of Multilingual Dictionaries on the Web—0
Data Ordering Patterns for Neural Machine Translation: An Empirical Study—0
Data Processing Matters: SRPH-Konvergen AI's Machine Translation System for WMT'21—0
Data Processing Matters: SRPH-Konvergen AI’s Machine Translation System for WMT’21—0
Critical Appraisal of Artificial Intelligence-Mediated Communication—0
Data representation methods and use of mined corpora for Indian language transliteration—0
Data Scaling Laws in NMT: The Effect of Noise and Architecture—0
Data Selection Curriculum for Neural Machine Translation—0
Data Selection for Bilingual Lexicon Induction from Specialized Comparable Corpora—0
Data Selection for IT Texts using Paragraph Vector—0
Data Selection for Unsupervised Translation of German–Upper Sorbian—0
Data Selection with Cluster-Based Language Difference Models and Cynical Selection—0
Data Selection with Feature Decay Algorithms Using an Approximated Target Side—0
Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation—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