Issue #129 – Simultaneous MT Using Imitation Learning
06 May21
Issue #129 – Simultaneous MT Using Imitation Learning
Author: Dr. Karin Sim, Machine Translation Scientist @ Iconic
Introduction
For the second time in our blog series we look at Simultaneous Machine Translation (SiMT). In SiMT, translation begins before the full source input has necessarily been processed, reducing the delay as much as possible. By necessity this results in a trade off between delay and MT quality. This subject was discussed in a previous blog post. The full pipe line tries to mimic that of a human interpreter and therefore requires automatic speech recognition, whereas the paper which is our focus today, Arthur et al. (2021), is limited to the MT functionality. Interestingly, the evaluation focuses on BLEU and latency, instead of quality.