Abstract:
Although the quality of machine translation (MT)
has improved in recent years, machine translated documents
still contain errors. MT quality is often evaluated using a single
numeric score. However, this may not adequately characterise the
system. We provide an error visualizer, which shows differences
between corresponding lines of two translations. In addition to
insertions, deletions and substitutions, our system also shows
transpositions. We also provide an error analyzer which gives
statistics of each type of error in the document. In addition, it
shows errors in context: the words commonly adjacent to each
error, and also the adjacent parts of speech (POS). This feature -
unique to our system - allows the identification of the context in
which errors occur, so they can be rectified easily. The system was
evaluated by three MT system developers, who identified useful
features and provided feedback which was used to improve the
system.
