This master's thesis examines the challenges and limitations of machine translation of humor using the animated series *Family Guy* as a case study. The focus is on comparing the official Hungarian translation of the punchlines, the machine translation produced by the DeepL neural translation system, and a post-edited version. The goal is to analyze the extent to which machine translation systems are capable of adequately conveying humorous content and to determine the role that human post-editing plays in this process.
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