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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
Beyond Parallel Data: Joint Word Alignment and Decipherment Improves Machine Translation—0
Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation—0
DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents—0
DOCAL - Vicomtech's Participation in the WMT16 Shared Task on Bilingual Document Alignment—0
Do all Roads Lead to Rome? Understanding the Role of Initialization in Iterative Back-Translation—0
Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation—0
A New Syntactic Metric for Evaluation of Machine Translation—0
A Formalized Reference Grammar for UNL-Based Machine Translation between English and Arabic—0
DMDTEval: An Evaluation and Analysis of LLMs on Disambiguation in Multi-domain Translation—0
DM-CT: Consistency Training with Data and Model Perturbation—0
Beyond Human-Only: Evaluating Human-Machine Collaboration for Collecting High-Quality Translation Data—0
DLS@CU: Sentence Similarity from Word Alignment—0
DLS@CU: Sentence Similarity from Word Alignment and Semantic Vector Composition—0
A New Semantic Lexicon and Similarity Measure in Bangla—0
DLS@CU at SemEval-2016 Task 1: Supervised Models of Sentence Similarity—0
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)—0
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation—0
Diving Deep into Context-Aware Neural Machine Translation—0
Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trust—0
A new semantically annotated corpus with syntactic-semantic and cross-lingual senses—0
A Formal Characterization of Parsing Word Alignments by Synchronous Grammars with Empirical Evidence to the ITG Hypothesis.—0
Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models—0
Diversity in Machine Learning—0
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter—0
A New Search Approach for Interactive-Predictive Computer-Assisted Translation—0
Diversity by Phonetics and its Application in Neural Machine Translation—0
Diversity and Language Technology: How Techno-Linguistic Bias Can Cause Epistemic Injustice—0
Diversifiable Bootstrapping for Acquiring High-Coverage Paraphrase Resource—0
Diverse Words, Shared Meanings: Statistical Machine Translation for Paraphrase, Grounding, and Intent—0
Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction—0
A New Parsing Algorithm for Combinatory Categorial Grammar—0
Diverse Machine Translation with a Single Multinomial Latent Variable—0
Divergences in English-Hindi Parallel Dependency Treebanks—0
A New Minimally-Supervised Framework for Domain Word Sense Disambiguation—0
Dive deeper: Deep Semantics for Sentiment Analysis—0
Distributional Properties of Subword Regularization—0
Distributed Representations for Unsupervised Semantic Role Labeling—0
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics—0
A New Massive Multilingual Dataset for High-Performance Language Technologies—0
A Flexible Approach to Automated RNN Architecture Generation—0
A Corpus for English-Japanese Multimodal Neural Machine Translation with Comparable Sentences—0
Distributed representation and estimation of WFST-based n-gram models—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Distortion Model Considering Rich Context for Statistical Machine Translation—0
DISTO: Evaluating Textual Distractors for Multi-Choice Questions using Negative Sampling based Approach—0
A new approach to calculating BERTScore for automatic assessment of translation quality—0
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach—0
Distinguishing Literal and Non-Literal Usage of German Particle Verbs—0
Distinguishing Japanese Non-standard Usages from Standard Ones—0
Distinguishing Degrees of Compositionality in Compound Splitting for Statistical Machine 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