In our lab meeting tomorrow, Ashkan will introduce his project on Machine Translation.
Policy in simultaneous Neural Machine Translation
Abstract: In simultaneous machine translation, finding optimal segments on the source and target side of each sentence pair that maintain translation quality while minimizing delay remains challenging. We propose a supervised learning approach for training an Agent that can detect the minimum number of reads required for generating each target token. By decoupling the training procedure of our Agent we can apply our policy on NMT components trained in various ways.
Tuesday, Feb 9th, 09:30 a.m.
