Search Results for author: Macduff Hughes

Found 7 papers, 3 papers with code

Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection

no code implementations WS 2018 Wei Wang, Taro Watanabe, Macduff Hughes, Tetsuji Nakagawa, Ciprian Chelba

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 Machine Translation +1

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation

4 code implementations TACL 2017 Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean

In addition to improving the translation quality of language pairs that the model was trained with, our models can also learn to perform implicit bridging between language pairs never seen explicitly during training, showing that transfer learning and zero-shot translation is possible for neural translation.

Machine Translation Transfer Learning +1

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