Guide
Audio Transcription and Translation
Most audio translation workflows combine two steps: converting speech to text (transcription) and converting that text into another language (translation). Understanding how these steps work helps you get more accurate, useful output.
Step 1 — Speech to text (transcription)
The AI listens to your audio and converts spoken words into written text. This is called automatic speech recognition (ASR). Modern AI models can handle accents, background noise, and multiple languages. The output is a timestamped transcript of everything spoken in the recording.
Accuracy depends on audio quality. Clear recordings with minimal background noise and a single speaker consistently reach very high accuracy. Overlapping voices, strong accents in unusual dialects, or heavy compression can reduce accuracy.
Step 2 — Text translation
Once the transcript exists, the AI translates it into your chosen target language. This is not a word-for-word substitution — the AI understands sentence structure, context, and meaning before producing a natural-sounding translation.
Translation works best when the source transcript is accurate. Errors in transcription carry forward into translation, which is why audio quality matters at step one.
Optional Step 3 — Voice dubbing
If you need spoken output rather than just text, enable voice dubbing. The AI synthesizes the translated text into speech using a natural AI voice in the target language. The result is a new audio file — same content, different language.
Which workflow should you use?
| Use case | Recommended mode |
|---|---|
| Meeting notes in another language | Transcript + Translation |
| Subtitles for a video | Transcript + Translation |
| Multilingual podcast episode | Transcript + Translation + Dubbing |
| Voiceover for an explainer video | Transcript + Translation + Dubbing |
| Customer support call review | Transcript + Translation |
| Language learning material | Transcript + Translation + Dubbing |
How credits are consumed
Credits are used by actual processing work. Transcription uses a base amount per minute of audio. Translation adds a smaller amount per word of output. Dubbing adds synthesis credits per word of spoken text generated. A short clip with transcript and translation only uses far fewer credits than a long recording with full dubbing enabled.
Accuracy tips
- Record at 16 kHz or higher sample rate for best ASR accuracy.
- Reduce room echo and background noise before uploading.
- For interviews: try to avoid speakers interrupting each other.
- Specify the source language instead of using auto-detect when you know it — this removes an inference step and reduces errors.
- For high-stakes content (legal, medical, compliance), always have a human review the translation output.
Try the full workflow
Upload audio and choose between transcript-only, translation, or full dubbing in one pass.
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