Exploring Massively Multilingual, Massive Neural Machine Translation
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Published on ● Video Link: https://www.youtube.com/watch?v=817hax8OL4M
We will be giving an overview of the recent efforts towards universal translation at Google Research. From training a single translation model for 100+ languages to scaling neural networks beyond 80 billion parameters with 1000 layers deep Transformers and several research and engineering challenges that the project has tackled; multi-task learning with hundreds of tasks, learning under heavy data imbalance, trainability of very deep networks, understanding the learned representations, cross-lingual down-stream transfer and many more insights will be shared.
See more at https://www.microsoft.com/en-us/research/video/exploring-massively-multilingual-massive-neural-machine-translation/
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Tags:
Machine Translation
Orhan Firat
Akiko Eriguchi
universal translation
scaling neural networks
multi-task learning
deep networks
microsoft research