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Speech models transcribe everyday words well but stumble on the unusual ones — coworker names, product names, acronyms, and technical jargon they’ve never heard. Vocabulary feeds those terms to the model before it transcribes, so it knows to expect them. Add a term like Kubernetes, Anthropic, or a colleague’s name, and the model is far more likely to spell it right instead of guessing at a phonetic lookalike.

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Vocabulary vs. dictionary

This is the key distinction, and it trips people up:

Vocabulary

Changes how your audio is heard. It biases the speech model before transcription so it recognizes tricky words. It’s a nudge, not a guarantee.

Dictionary

Rewrites text after transcription. It’s an exact, deterministic find-and-replace. See Dictionary.
Rule of thumb: use vocabulary to help the model hear a word, and the dictionary to force an exact spelling or expansion.

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Add a term

1

Open Vocabulary

Find it in the sidebar.
2

Add the term

Enter the word or phrase (up to 200 characters). Optionally add a note to remind yourself what it is — notes are for your own reference and aren’t sent to the model.
You can search terms and import or export them as JSON (up to 1,000 entries per import).

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Model support varies

Vocabulary is only as good as the speech model’s support for it, and that differs by provider. Freestyle sends terms in whatever form each model accepts, and the Vocabulary page tells you what your current model supports.
Because there’s a size budget, only your most relevant terms are sent when the list is long. Keep the list focused on words the model actually gets wrong.

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When it runs

Vocabulary is the first step in the pipeline — it shapes the transcription itself, before any cleanup or dictionary replacement happens.