Google Neural Machine Translation - a podcast by Ben Jaffe and Katie Malone

Recently, Google swapped out the backend for Google Translate, moving from a statistical phrase-based method to a recurrent neural network. This marks a big change in methodology: the tried-and-true statistical translation methods that have been in use for decades are giving way to a neural net that, across the board, appears to be giving more fluent and natural-sounding translations. This episode recaps statistical phrase-based methods, digs into the RNN architecture a little bit, and recaps the impressive results that is making us all sound a little better in our non-native languages.

Further episodes of Linear Digressions

Further podcasts by Ben Jaffe and Katie Malone

Website of Ben Jaffe and Katie Malone