NMT
489 papers with code • 0 benchmarks • 1 datasets
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.
Benchmarks
These leaderboards are used to track progress in NMT
Libraries
Use these libraries to find NMT models and implementationsMost implemented papers
Effective Approaches to Attention-based Neural Machine Translation
Our ensemble model using different attention architectures has established a new state-of-the-art result in the WMT'15 English to German translation task with 25. 9 BLEU points, an improvement of 1. 0 BLEU points over the existing best system backed by NMT and an n-gram reranker.
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
To improve parallelism and therefore decrease training time, our attention mechanism connects the bottom layer of the decoder to the top layer of the encoder.
Neural Machine Translation of Rare Words with Subword Units
Neural machine translation (NMT) models typically operate with a fixed vocabulary, but translation is an open-vocabulary problem.
Sockeye: A Toolkit for Neural Machine Translation
Written in Python and built on MXNet, the toolkit offers scalable training and inference for the three most prominent encoder-decoder architectures: attentional recurrent neural networks, self-attentional transformers, and fully convolutional networks.
Phrase-Based & Neural Unsupervised Machine Translation
Machine translation systems achieve near human-level performance on some languages, yet their effectiveness strongly relies on the availability of large amounts of parallel sentences, which hinders their applicability to the majority of language pairs.
Massive Exploration of Neural Machine Translation Architectures
Neural Machine Translation (NMT) has shown remarkable progress over the past few years with production systems now being deployed to end-users.
OpenNMT: Neural Machine Translation Toolkit
OpenNMT is an open-source toolkit for neural machine translation (NMT).
Joey NMT: A Minimalist NMT Toolkit for Novices
We present Joey NMT, a minimalist neural machine translation toolkit based on PyTorch that is specifically designed for novices.
Sequence-Level Knowledge Distillation
We demonstrate that standard knowledge distillation applied to word-level prediction can be effective for NMT, and also introduce two novel sequence-level versions of knowledge distillation that further improve performance, and somewhat surprisingly, seem to eliminate the need for beam search (even when applied on the original teacher model).
THUMT: An Open Source Toolkit for Neural Machine Translation
This paper introduces THUMT, an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University.