5.7k citations · 6k across the 4 of their papers we have counts for
4 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…
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…