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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 1001–1050 of 1773 papers

TitleStatusHype
Findings of the Fourth Workshop on Neural Generation and Translation—0
Improving Neural Machine Translation with Soft Template Prediction—0
Language-aware Interlingua for Multilingual Neural Machine Translation—0
Pre-training via Leveraging Assisting Languages for Neural Machine Translation—0
Uncertainty-Aware Curriculum Learning for Neural Machine Translation—0
The HW-TSC Video Speech Translation System at IWSLT 2020—0
FFR v1.1: Fon-French Neural Machine Translation—0
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—0
Modeling Baroque Two-Part Counterpoint with Neural Machine TranslationCode0
Learning Source Phrase Representations for Neural Machine Translation—0
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation—0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
HausaMT v1.0: Towards English-Hausa Neural Machine Translation—0
Universal Vector Neural Machine Translation With Effective Attention—0
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
Modeling Discourse Structure for Document-level Neural Machine Translation—0
Enhanced back-translation for low resource neural machine translation using self-training—0
Is 42 the Answer to Everything in Subtitling-oriented Speech Translation?—0
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-EnglishCode0
Neural Simultaneous Speech Translation Using Alignment-Based Chunking—0
Variational Neural Machine Translation with Normalizing Flows—0
The Unreasonable Volatility of Neural Machine Translation ModelsCode0
Character-level Transformer-based Neural Machine Translation—0
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation—0
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages—0
DiscreTalk: Text-to-Speech as a Machine Translation Problem—0
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation—0
Neural Machine Translation for South Africa's Official Languages—0
Evaluating Explanation Methods for Neural Machine Translation—0
Using Context in Neural Machine Translation Training Objectives—0
A Comprehensive Survey of Grammar Error Correction—0
The Learnability of the Annotated Input in NMT Replicating (Vanmassenhove and Way, 2018) with OpenNMT—0
Linguistically Informed Hindi-English Neural Machine Translation—0
Corpora for Document-Level Neural Machine Translation—0
Multiword Expression aware Neural Machine Translation—0
Being Generous with Sub-Words towards Small NMT Children—0
Multilingual Neural Machine Translation involving Indian Languages—0
NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations—0
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts—0
Building a Task-oriented Dialog System for Languages with no Training Data: the Case for Basque—0
Evaluating Robustness to Input Perturbations for Neural Machine Translation—0
Mirror-Generative Neural Machine Translation—0
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages—0
OdiEnCorp 2.0: Odia-English Parallel Corpus for Machine Translation—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
FrameNet Annotations Alignment using Attention-based Machine Translation—0
Construction of an Evaluation Corpus for Grammatical Error Correction for Learners of Japanese as a Second Language—0
Much Ado About Nothing -- Identification of Zero Copulas in Hungarian Using an NMT Model—0
Improving NMT Quality Using Terminology Injection—0
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