5.7k citations · 5.8k across the 5 of their papers we have counts for
6 papers
Building Machine Translation Systems for the Next Thousand Languages
Ankur Bapna, Isaac Caswell, Julia Kreutzer +21
In this paper we share findings from our effort to build practical machine translation (MT) systems capable of translating across over one thousand languages. We describe results i…
TICO-19: the Translation Initiative for Covid-19
Antonios Anastasopoulos, Alessandro Cattelan, Zi-Yi Dou +15
The COVID-19 pandemic is the worst pandemic to strike the world in over a century. Crucial to stemming the tide of the SARS-CoV-2 virus is communicating to vulnerable populations t…
Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection
Wei Wang, Taro Watanabe, Macduff Hughes +2
Measuring domain relevance of data and identifying or selecting well-fit domain data for machine translation (MT) is a well-studied topic, but denoising is not yet. Denoising is co…
The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation
Mia Xu Chen, Orhan Firat, Ankur Bapna +9
The past year has witnessed rapid advances in sequence-to-sequence (seq2seq) modeling for Machine Translation (MT). The classic RNN-based approaches to MT were first out-performed…
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
Melvin Johnson, Mike Schuster, Quoc V. Le +9
We propose a simple solution to use a single Neural Machine Translation (NMT) model to translate between multiple languages. Our solution requires no change in the model architectu…
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu, Mike Schuster, Zhifeng Chen +28
Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based tr…