How I use an LLM as a translation judge

📰 Dev.to AI

Learn how to use an LLM as a translation judge to evaluate translation quality in a live speech-to-speech translation pipeline

intermediate Published 22 May 2026
Action Steps
  1. Use GEMBA-MQM v2 to evaluate translation quality
  2. Configure the LLM to classify errors by type and severity using MQM
  3. Integrate the LLM into your live speech-to-speech translation pipeline
  4. Test the LLM's annotation process using sample translations
  5. Compare the LLM's evaluations with human judgments to fine-tune its performance
Who Needs to Know This

Translation teams and developers working on speech-to-speech translation pipelines can benefit from using an LLM as a translation judge to improve translation quality

Key Insight

💡 LLMs can be used to evaluate translation quality using open industry standards like MQM, reducing the need for manual human review

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