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Ask ChatGPT – June 27, 2024

Ask ChatGPT
My Conversations with ChatGPT
Machine Translation (MT) and translations generated by AI have brought about a paradigm shift in the translation industry. The output of MT will continue to improve, especially when associated with clients’ translation memories and human editing. Language Service Providers are adapting and are including MT in their processes, when MT is applicable. While linguists will continue to be essential in the process, their role will shift from that of translators to validators of content generated by MT. At Excel Translations, we wanted to know what AI thinks about all of this and decided to have an open conversation on the matter with ChatGPT. I will regularly publish a question and ChatGPT’s response, uncensored.

QUESTION 163:

Is domain-specific-knowledge something to be concerned about with machine translation?

Chat GPT’s Response:

Yes, domain-specific knowledge is a significant concern with machine translation. Here are some key reasons why:

Accuracy and Context:

Technical Terms: Different domains use specific terminology that may not be accurately translated by general-purpose machine translation systems. For instance, medical, legal, and technical texts often contain jargon that requires precise understanding to translate correctly.

Contextual Understanding: General machine translation systems may fail to grasp the context in which certain terms are used, leading to incorrect or awkward translations. Domain-specific knowledge helps ensure that the context is correctly interpreted.

Consistency:

Terminology Consistency: In specialized fields, maintaining consistency in the translation of terms is crucial. For example, in software documentation, the same technical term must be translated consistently across all documents to avoid confusion.

tyle and Tone: Different domains may require different styles and tones. For example, legal documents need to be formal and precise, while marketing content might be more engaging and persuasive.

Reliability:

Error Reduction: The lack of domain-specific knowledge can lead to errors that are not just embarrassing but potentially dangerous, especially in fields like healthcare or aviation where precision is critical.

Regulatory Compliance: Certain domains require adherence to specific regulatory standards. Translations in these fields must meet these standards to ensure compliance and avoid legal issues.

Efficiency:

Post-Editing Workload: When machine translation systems lack domain-specific knowledge, the burden on human translators to post-edit and correct translations increases, negating some of the efficiency gains from using machine translation.

Cultural Nuances:

Localization: Domain-specific translations often need to be localized, not just translated. This means adapting the content to fit the cultural and practical norms of the target audience, which requires deep domain knowledge.

In summary, ensuring machine translation systems incorporate domain-specific knowledge is crucial for accuracy, consistency, reliability, efficiency, and cultural relevance. This often requires training models on specialized datasets and involving human experts for quality assurance.

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