5.7k citations · 6k across the 5 of their papers we have counts for
5 papers
Direct speech-to-speech translation with a sequence-to-sequence model
Ye Jia, Ron J. Weiss, Fadi Biadsy +4
We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an inter…
The Missing Ingredient in Zero-Shot Neural Machine Translation
Naveen Arivazhagan, Ankur Bapna, Orhan Firat +3
Multilingual Neural Machine Translation (NMT) models are capable of translating between multiple source and target languages. Despite various approaches to train such models, they…
Massively Multilingual Neural Machine Translation
Roee Aharoni, Melvin Johnson, Orhan Firat
Multilingual neural machine translation (NMT) enables training a single model that supports translation from multiple source languages into multiple target languages. In this paper…
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Jonathan Shen, Patrick Nguyen, Yonghui Wu +88
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…
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…