# Dictation post-process

**Source:** https://promtable.com/glossary/dictation-postprocess

> Dictation post-process is the LLM step that cleans raw transcription into polished text — adds punctuation + paragraphs, removes filler words, fixes grammar, expands abbreviations, applies user style. The reason modern dictation feels magical vs system dictation.

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Dictation post-process is the LLM step that cleans raw transcription into polished text — adds punctuation + paragraphs, removes filler words, fixes grammar, expands abbreviations, applies user style. The reason modern dictation feels magical vs system dictation.

Raw Whisper transcription is good but raw — no smart paragraphing, occasional filler ('umm', 'you know'), inconsistent punctuation. Post-process pipes the raw text through an LLM with a prompt: 'clean this up, add punctuation + paragraphs, remove filler, preserve meaning'. Optional: domain-aware style prompts ('this is a Slack DM, keep casual'), per-app modes (formal email vs casual text vs commit message), custom vocab dictionaries for proper nouns. Wispr Flow / Superwhisper bake this in. Trade-offs: LLM can hallucinate words not actually said (especially proper nouns), latency adds ~500ms. The right mode for a given app is the difference between dictation feeling natural and feeling robotic.

## When to use

- Any production dictation app.

## Common mistakes

- Skipping post-process — feels like 2010 dictation.
- Over-prompting — LLM rewrites too aggressively, loses user voice.

## Related terms

- [voice-dictation](https://promtable.com/glossary/voice-dictation)
- [streaming-stt](https://promtable.com/glossary/streaming-stt)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/dictation-postprocess
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