In our lab meeting this week, Hassan will talk about handling out-of-domain and out-of-vocabulary words in NMT. The title and abstract of the talk:
Imposing Bilingual Lexical Constraints to Neural Machine Translation
Abstract: eural Machine Translation (NMT) models have reached astonishing results in recent years, and yet infrequent words remain a problem to them as well as out-of-domain terminologies. Bilingual lexical resources can be used to guide the model through difficulties when it faces infrequent and out-of-domain vocabulary words. Hence, imposing bilingual lexical preferences (constraints) into NMT models have received rising attention in the past few years. In this talk, we summarize different threads of work on Constrained NMT including approaches that modify the input or output of the model (pre-processing and post-processing) without changing the model itself, as well as, the approaches that change the inference algorithms and target vocabulary set.
Tuesday, September 23rd, 10:30 a.m. TASC1 9408.