The common failure mode
If you force a single language on a recording that switches languages, you often get:
- misspelled names and “broken” words
- wrong punctuation patterns
- low-quality translation (because the base transcript is unstable)
Use auto-detect (multi-language)
Auto-detect allows the model to pick the best language for each segment. If confidence is low, a robust workflow tries additional candidates.
Practical tips
- Enhance audio first (noise reduction + normalization). Cleaner audio improves language confidence.
- If the recording switches only once (e.g., intro in Arabic, talk in English), split the file and run two jobs.
When NOT to use auto
If the recording is 95% one language, forcing that language can be faster and more stable.
Summary
Multi-language auto-detect is not magic, but it’s the right default for mixed-language meetings, interviews, and podcasts.