Machine Translation (MT) engines have become increasingly sophisticated, but they are not foolproof. They often produce pre-translated texts that, while roughly accurate, still contain errors that can affect the meaning, tone, and fluency of the output. Professional translators are familiar with these typical errors and are trained to identify and correct them during the post-editing process. Here are some of the common types of errors found in machine-translated texts:

1. Literal Translations: MT engines may translate text word-for-word without considering context or idiomatic usage. This can result in nonsensical or awkward sentences because the engine fails to capture the intended meaning or nuance.

2. Terminology Inconsistencies: Machines may not consistently apply the correct technical or industry-specific terminology. They might choose synonyms that seem right but are inappropriate for the context, or they might fail to recognize when a term should remain untranslated (e.g., brand names or concepts without equivalents).

3. Grammar and Syntax Errors: MT may struggle with complex grammar structures, such as long sentences with multiple clauses, passive voice, or nuanced verb tenses. It might incorrectly structure sentences, leading to confusion about subjects, objects, and their actions.

4. Colloquialisms and Idioms: MT engines typically cannot understand idiomatic expressions or slang that are culture-specific. They may either translate these expressions literally or misinterpret them entirely.

5. Punctuation and Formatting: MT can erroneously interpret punctuation marks, leading to run-on sentences, incorrect sentence splitting, or other issues that affect readability. It can also ignore formatting nuances important for the text's meaning, such as bullet points, italics, or bold text.

6. Named Entity Errors: MT might incorrectly translate proper nouns, including names of people, places, organizations, and sometimes even dates and numbers. This can lead to confusion, especially if the named entity has a specific significance within the text.

7. Ambiguity and Polysemy: Words with multiple meanings (polysemous words) pose a significant challenge for MT, as it may not choose the correct meaning in a given context. Similarly, ambiguously phrased sentences can lead to inaccurate translations.

8. Consistency Problems: MT might not maintain consistent terminology or style throughout a document. This inconsistency can confuse the reader and detract from the text's professionalism.

9. Cultural Nuances: MT engines may not account for cultural subtleties, potentially leading to translations that are culturally insensitive or inappropriate. Cultural references, humour, and politeness levels are often lost or misrepresented.

10. Homophones and Homographs: MT might confuse words that sound alike (homophones) or words that are spelled the same but have different meanings (homographs), especially in languages where such nuances are context-dependent.

Identifying and correcting these errors is a critical component of the post-editing process. MT engines are tools that can streamline the translation process, but the expertise of a human translator is indispensable for creating polished, accurate, and culturally relevant translations. As MT technology continues to develop, the role of the human translator is not diminished but rather enhanced, with a focus on nuanced editing and quality assurance to deliver the best possible final product.