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We describe the joint submission of the University of Edinburgh and Charles University, Prague, to the Czech/English track in the WMT 2020 Shared Task on News Translation. Our fast and compact student models distill knowledge from a larger, slower teacher. They are designed to offer a good trade-off between translation quality and inference efficiency. On the WMT 2020 Czech â†” English test sets, they achieve translation speeds of over 700 whitespace-delimited source words per second on a single CPU thread, thus making neural translation feasible on consumer hardware without a GPU.
|Title of host publication||Proceedings of the Fifth Conference on Machine Translation|
|Place of Publication||Online|
|Publisher||Association for Computational Linguistics|
|Number of pages||6|
|Publication status||Published - 19 Nov 2020|