stat946w18/Synthetic and natural noise both break neural machine translation

Introduction

• Humans have surprisingly robust language processing systems which can easily overcome typos, e.g.

Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer in waht oredr the ltteers in a wrod are, the olny iprmoetnt tihng is taht the frist and lsat ltteer be at the rghit pclae.

• A person's ability to read this text comes as no surprise to the Psychology literature
  1. Saberi \& Perrott (1999) found that this robustness extends to audio as well.
  2. Rayner et al. (2006) found that in noisier settings reading comprehension only slowed by 11 \%.
  3. McCusker et al. (1981) found that the common case of swapping letters could often go unnoticed by the reader.
  4. Mayall et al (1997) shows that we rely on word shape.
  5. Reicher, 1969; Pelli et al., (2003) found that we can switch between whole word recognition but the first and last letter positions are required to stay constant for comprehension

However, NMT(neural machine translation) systems are brittle. i.e. The Arabic word