Emotion Profiling in LLM-Based Literary Translation: Systematic Shifts Across MT and Post-Editing
A new research paper explores the emotional characteristics of translations produced by Large Language Models (LLMs). The study compares LLM translations of Margaret Atwood's "Oryx and Crake" with human translations and post-edited versions. Findings indicate that LLMs imprint distinct emotional patterns on their translations, which can obscure the original author's voice and are only partially corrected by human post-editing. AI
IMPACT Reveals how LLMs may alter authorial voice in translation, impacting literary authenticity and the effectiveness of post-editing.