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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 5151–5200 of 10752 papers

TitleStatusHype
Exploring the Robustness of NMT Systems to Nonsensical Inputs—0
The TALP-UPC System for the WMT Similar Language Task: Statistical vs Neural Machine Translation—0
Self-Knowledge Distillation in Natural Language Processing—0
FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow SystemCode0
Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the "Wrong" Predictions—0
Leveraging SNOMED CT terms and relations for machine translation of clinical texts from Basque to Spanish—0
With or without post-editing processes? Evidence for a gap in machine translation evaluation—0
Factored Neural Machine Translation at LoResMT 2019—0
Sentence-Level Adaptation for Low-Resource Neural Machine Translation—0
Machine Translation for Crimean Tatar to Turkish—0
MAGMATic: A Multi-domain Academic Gold Standard with Manual Annotation of Terminology for Machine Translation Evaluation—0
Applying Machine Translation to Psychology: Automatic Translation of Personality Adjectives—0
Evaluating machine translation in a low-resource language combination: Spanish-Galician.—0
Application of Post-Edited Machine Translation in Fashion eCommerce—0
Multilingual Multimodal Machine Translation for Dravidian Languages utilizing Phonetic Transcription—0
Neural Machine Translation of Literary Texts from English to Slovene—0
Do translator trainees trust machine translation? An experiment on post-editing and revision—0
Leveraging Rule-Based Machine Translation Knowledge for Under-Resourced Neural Machine Translation Models—0
Pre-editing Plus Neural Machine Translation for Subtitling: Effective Pre-editing Rules for Subtitling of TED Talks—0
An Exploration of Placeholding in Neural Machine Translation—0
A3-108 Machine Translation System for LoResMT 2019—0
Proceedings of Machine Translation Summit XVII Volume 1: Research Track—0
A Continuous Improvement Framework of Machine Translation for Shipibo-Konibo—0
Developing a Neural Machine Translation system for Irish—0
Decision-making, Risk, and Gist Machine Translation in the Work of Patent Professionals—0
Proceedings of the Qualities of Literary Machine Translation—0
The Challenges of Using Neural Machine Translation for Literature—0
When less is more in Neural Quality Estimation of Machine Translation. An industry case study—0
Leveraging backtranslation to improve machine translation for Gaelic languages—0
Translation Quality and Effort Prediction in Professional Machine Translation Post-Editing—0
Neural machine translation system for the Kazakh language—0
Pivot Machine Translation in INTERACT Project—0
Large-scale Machine Translation Evaluation of the iADAATPA Project—0
Improving Neural Machine Translation Using Noisy Parallel Data through Distillation—0
WordNet Gloss Translation for Under-resourced Languages using Multilingual Neural Machine Translation—0
Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks—0
Improving Domain Adaptation for Machine Translation withTranslation Pieces—0
Improving Anaphora Resolution in Neural Machine Translation Using Curriculum Learning—0
Controlling the Reading Level of Machine Translation Output—0
A Multi-Hop Attention for RNN based Neural Machine Translation—0
Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation—0
Hungarian translators' perceptions of Neural Machine Translation in the European Commission—0
A step towards Torwali machine translation: an analysis of morphosyntactic challenges in a low-resource language—0
Machine Translation in the Financial Services Industry: A Case Study—0
Competitiveness Analysis of the European Machine Translation Market—0
Proceedings of the Second Workshop on Multilingualism at the Intersection of Knowledge Bases and Machine Translation—0
User expectations towards machine translation: A case study—0
NICT's Machine Translation Systems for the WMT19 Similar Language Translation Task—0
Meteor++ 2.0: Adopt Syntactic Level Paraphrase Knowledge into Machine Translation Evaluation—0
Findings of the WMT 2019 Shared Tasks on Quality Estimation—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