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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 1051–1100 of 10752 papers

TitleStatusHype
A Procedural Definition of Multi-word Lexical Units—0
A Joint Sequential and Relational Model for Frame-Semantic Parsing—0
A Bayesian Approach to Unsupervised Semantic Role Induction—0
Findings of the Third Workshop on Neural Generation and Translation—0
A Unified Neural Coherence Model—0
A Probabilistic Approach to Persian Ezafe Recognition—0
APRO: All-Pairs Ranking Optimization for MT Tuning—0
A Joint Model of Orthography and Morphological Segmentation—0
A Principled Approach to Context-Aware Machine Translation—0
A Primer in NMTology: What we have understood about NMT—0
A Joint Model for Unsupervised Chinese Word Segmentation—0
Adaptation of Statistical Machine Translation Model for Cross-Lingual Information Retrieval in a Service Context—0
A Preordered RNN Layer Boosts Neural Machine Translation in Low Resource Settings—0
A Preliminary Study on Mandarin-Hakka neural machine translation using small-sized data—0
A joint inference of deep case analysis and zero subject generation for Japanese-to-English statistical machine translation—0
A Preliminary Study of Croatian Lexical Substitution—0
A Preliminary Study for Building an Arabic Corpus of Pair Questions-Texts from the Web: AQA-Webcorp—0
A Joint Dependency Model of Morphological and Syntactic Structure for Statistical Machine Translation—0
Adaptation of Reordering Models for Statistical Machine Translation—0
Accurate Evaluation of Segment-level Machine Translation Metrics—0
A Practical Chinese-English ON Translation Method Based on ON`s Distribution Characteristics on the Web—0
Approximate Sentence Retrieval for Scalable and Efficient Example-Based Machine Translation—0
A Joint Chinese Named Entity Recognition and Disambiguation System—0
Approximate Distribution Matching for Sequence-to-Sequence Learning—0
Approches quantitatives de l'analyse des prédictions en traduction automatique neuronale (TAN)—0
A Joint Approach to Compound Splitting and Idiomatic Compound Detection—0
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods—0
Approches d'analyse distributionnelle pour améliorer la désambiguïsation sémantique—0
Approaching Sign Language Gloss Translation as a Low-Resource Machine Translation Task—0
A Japanese Word Dependency Corpus—0
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task—0
Airport Announcement System for Deaf—0
Accurate Cross-lingual Projection between Count-based Word Vectors by Exploiting Translatable Context Pairs—0
A Bayesian approach to translators' reliability assessment—0
A Unified Kernel Approach for Learning Typed Sentence Rewritings—0
A Universal Parent Model for Low-Resource Neural Machine Translation Transfer—0
Automated Paraphrase Lattice Creation for HyTER Machine Translation Evaluation—0
Automatic Classification of Human Translation and Machine Translation: A Study from the Perspective of Lexical Diversity—0
Approaching English-Polish Machine Translation Quality Assessment with Neural-based Methods—0
Appraise Evaluation Framework for Machine Translation—0
AI in Support of Diversity and Inclusion—0
Applying the Cognitive Machine Translation Evaluation Approach to Arabic—0
Applying Statistical Post-Editing to English-to-Korean Rule-based Machine Translation System—0
Adaptation of a Rule-Based Translator to R\' de la Plata Spanish—0
Augmenting String-to-Tree and Tree-to-String Translation with Non-Syntactic Phrases—0
Applying Sanskrit Concepts for Reordering in MT—0
Applying Pairwise Ranked Optimisation to Improve the Interpolation of Translation Models—0
AIDA2: A Hybrid Approach for Token and Sentence Level Dialect Identification in Arabic—0
Applying Neural Networks to English-Chinese Named Entity Transliteration—0
Adaptation incr\'ementale de mod\`eles de traduction neuronaux (Incremental adaptation of neural machine translation models)—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