Abstract
We present the results of prototypical ex-
periments conducted with the goal of de-
signing a machine translation (MT) based
system that assists the annotators of
learner corpora in performing ortho-
graphic error annotation. When an anno-
tator marks a span of text as erroneous,
the system suggests a correction for the
marked error. The presented experiments
rely on word-level and character-level
Statistical Machine Translation (SMT)
systems.