POST-EDITING AND ITS MAJOR PROBLEMS IN MACHINE TRANSLATION

Abstract

Machine Translation Post-Editing (MTPE) has become a standard workflow in the language industry because neural machine translation (NMT) often delivers fluent drafts that still require human correction for accuracy, style, and compliance. However, post-editing is not simply “fixing small mistakes.” It introduces major problems such as hidden adequacy errors (omissions/additions), hallucinated content, terminology inconsistency, and high cognitive effort caused by repeatedly diagnosing meaning rather than rewriting freely. Research shows that post-editing time and pauses correlate with cognitive effort and vary depending on error types and context. The standard also formalizes post-editing as a professional process and defines requirements for full human post-editing and post-editor competence, confirming that MTPE is a specialized task rather than casual correction. article explains core MTPE problems, illustrates typical error patterns with examples, and proposes practical controls for safer, faster, and more reliable post-editing.