5.7k citations · 6.7k across the 20 of their papers we have counts for
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Leveraging Weakly Supervised Data to Improve End-to-End Speech-to-Text Translation
Ye Jia, Melvin Johnson, Wolfgang Macherey +6
End-to-end Speech Translation (ST) models have many potential advantages when compared to the cascade of Automatic Speech Recognition (ASR) and text Machine Translation (MT) models…
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation
Akiko Eriguchi, Melvin Johnson, Orhan Firat +2
Transferring representations from large supervised tasks to downstream tasks has shown promising results in AI fields such as Computer Vision and Natural Language Processing (NLP).…
Revisiting Character-Based Neural Machine Translation with Capacity and Compression
Colin Cherry, George Foster, Ankur Bapna +2
Translating characters instead of words or word-fragments has the potential to simplify the processing pipeline for neural machine translation (NMT), and improve results by elimina…
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…