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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 1851–1900 of 10752 papers

TitleStatusHype
Challenges in Adaptive Neural Machine Translation—0
Arabic Dialect Identification Using iVectors and ASR Transcripts—0
Challenges in Creating a Multilingual Sentiment Analysis Application for Social Media Mining—0
Challenges in Speech Recognition and Translation of High-Value Low-Density Polysynthetic Languages—0
Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study—0
Challenges of Building Domain-Specific Parallel Corpora from Public Administration Documents—0
Challenges of Computational Processing of Code-Switching—0
Challenges of Neural Machine Translation for Short Texts—0
Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging—0
Character Alignment in Morphologically Complex Translation Sets for Related Languages—0
Character and Subword-Based Word Representation for Neural Language Modeling Prediction—0
Character-Aware Decoder for Translation into Morphologically Rich Languages—0
Character-Aware Neural Networks for Arabic Named Entity Recognition for Social Media—0
Character-based Decoding in Tree-to-Sequence Attention-based Neural Machine Translation—0
Character-based Neural Machine Translation—0
Character-based Neural Machine Translation—0
Character-based Neural Machine Translation—0
Character-Based Pivot Translation for Under-Resourced Languages and Domains—0
Character-Cluster-Based Segmentation using Monolingual and Bilingual Information for Statistical Machine Translation—0
AraFinNLP 2024: The First Arabic Financial NLP Shared Task—0
Backward and Forward Language Modeling for Constrained Sentence Generation—0
Characterizing Departures from Linearity in Word Translation—0
AraNLP: a Java-based Library for the Processing of Arabic Text.—0
Character-Level Machine Translation Evaluation for Languages with Ambiguous Word Boundaries—0
AR: Auto-Repair the Synthetic Data for Neural Machine Translation—0
Character-level NMT and language similarity—0
Character-level Transformer-based Neural Machine Translation—0
Character-Level Translation with Self-attention—0
Character Mapping and Ad-hoc Adaptation: Edinburgh's IWSLT 2020 Open Domain Translation System—0
Character n-gram Embeddings to Improve RNN Language Models—0
Character Sequence-to-Sequence Model with Global Attention for Universal Morphological Reinflection—0
CharacTer: Translation Edit Rate on Character Level—0
Back-Translation-Style Data Augmentation for Mandarin Chinese Polyphone Disambiguation—0
Charles Translator: A Machine Translation System between Ukrainian and Czech—0
An empirical study on the effectiveness of images in Multimodal Neural Machine Translation—0
Chasing the Perfect Splitter: A Comparison of Different Compound Splitting Tools—0
Back-Translation-Style Data Augmentation for End-to-End ASR—0
Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation—0
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages—0
Cheat Codes to Quantify Missing Source Information in Neural Machine Translation—0
Cheat Codes to Quantify Missing Source Information in Neural Machine Translation—0
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems—0
Checks and Strategies for Enabling Code-Switched Machine Translation—0
Chimera -- Three Heads for English-to-Czech Translation—0
Are AI agents the new machine translation frontier? Challenges and opportunities of single- and multi-agent systems for multilingual digital communication—0
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese—0
Chinese Comma Disambiguation for Discourse Analysis—0
Chinese Grammatical Error Diagnosis System Based on Hybrid Model—0
Chinese Hypernym-Hyponym Extraction from User Generated Categories—0
An Empirical study of Unsupervised Neural Machine Translation: analyzing NMT output, model's behavior and sentences' contribution—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