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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 4101–4150 of 10752 papers

TitleStatusHype
Unleashing the Power of Neural Discourse Parsers -- A Context and Structure Aware Approach Using Large Scale Pretraining—0
Understanding Pure Character-Based Neural Machine Translation: The Case of Translating Finnish into English—0
Data Augmentation and Terminology Integration for Domain-Specific Sinhala-English-Tamil Statistical Machine Translation—0
Optimizing Transformer for Low-Resource Neural Machine Translation—0
Cross-Lingual Machine Speech Chain for Javanese, Sundanese, Balinese, and Bataks Speech Recognition and Synthesis—0
Streaming Attention-Based Models with Augmented Memory for End-to-End Speech Recognition—0
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles—0
Layer-Wise Multi-View Learning for Neural Machine Translation—0
Double Attention-based Multimodal Neural Machine Translation with Semantic Image RegionsCode0
Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial AttacksCode0
Subword Segmentation and a Single Bridge Language Affect Zero-Shot Neural Machine Translation—0
Cross-lingual Word Embeddings beyond Zero-shot Machine Translation—0
Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation—0
Enabling Zero-shot Multilingual Spoken Language Translation with Language-Specific Encoders and Decoders—0
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning—0
An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution—0
The 2020s Political Economy of Machine Translation—0
Natural Language Response Generation from SQL with Generalization and Back-translation—0
Alignment-free Cross-lingual Semantic Role Labeling—0
From Disjoint Sets to Parallel Data to Train Seq2Seq Models for Sentiment Transfer—0
Combining Sequence Distillation and Transfer Learning for Efficient Low-Resource Neural Machine Translation Models—0
UdS-DFKI@WMT20: Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian—0
Combination of Neural Machine Translation Systems at WMT20—0
A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning—0
Fine-Tuning MT systems for Robustness to Second-Language Speaker VariationsCode0
Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation—0
Coding Textual Inputs Boosts the Accuracy of Neural NetworksCode0
Fine-Grained Error Analysis on English-to-Japanese Machine Translation in the Medical Domain—0
Findings of the WMT 2020 Shared Tasks in Unsupervised MT and Very Low Resource Supervised MT—0
Two-Phase Cross-Lingual Language Model Fine-Tuning for Machine Translation Quality Estimation—0
Findings of the WMT 2020 Shared Task on Quality Estimation—0
Findings of the WMT 2020 Shared Task on Automatic Post-Editing—0
Findings of the WMT 2020 Shared Task on Machine Translation Robustness—0
Findings of the First Shared Task on Lifelong Learning Machine Translation—0
Alibaba Submission to the WMT20 Parallel Corpus Filtering Task—0
Alibaba’s Submission for the WMT 2020 APE Shared Task: Improving Automatic Post-Editing with Pre-trained Conditional Cross-Lingual BERT—0
Factorized Transformer for Multi-Domain Neural Machine Translation—0
The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT—0
NICE: Neural Integrated Custom Engines—0
Tencent submission for WMT20 Quality Estimation Shared Task—0
Extended Study on Using Pretrained Language Models and YiSi-1 for Machine Translation Evaluation—0
CEF Data Marketplace: Powering a Long-term Supply of Language Data—0
Exploring Coreference Features in Heterogeneous Data—0
Revisiting Representation Degeneration Problem in Language Modeling—0
Machine Translation Quality: A comparative evaluation of SMT, NMT and tailored-NMT outputs—0
The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task—0
The ADAPT System Description for the WMT20 News Translation Task—0
The NiuTrans System for the WMT20 Quality Estimation Shared Task—0
Monolingual Adapters for Zero-Shot Neural Machine Translation—0
Machine Translation Reference-less Evaluation using YiSi-2 with Bilingual Mappings of Massive Multilingual Language Model—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