Add words to your personal dictionary¶
Whisper sometimes mis-spells names, technical terms, or acronyms it hasn't seen in context — Kubernetes comes out as "Cuber Netties", a colleague's name gets mangled. Your personal dictionary fixes that: the words you add are primed into the STT prompt so recognition is biased toward spelling them correctly.
The dictionary lives in a plain text file, one word or phrase per line, at:
(On macOS it is under ~/Library/Application Support/yazses/, on Windows under %APPDATA%\yazses\.)
Add words¶
yazses vocab add YazSes # add one name
yazses vocab add Kubernetes kubectl # add several at once
yazses restart # apply so STT spells them right
Adding is case-insensitively de-duplicated, so re-adding a word is harmless. After adding, yazses restart reloads the daemon with the updated prompt.
List and remove¶
yazses vocab list # show every word in the dictionary
yazses vocab remove kubectl # drop a word
yazses restart # apply the removal
How it works — and its limits¶
The dictionary words are merged into Whisper's initial_prompt. That biases recognition; it does not force it. A soft prompt nudges the decoder toward your terms but a badly mis-heard word can still slip through, especially rare proper nouns spoken quickly.
For stubborn terms, two stronger, related mechanisms exist:
-
[stt] initial_promptinconfig.tomlis a free-form context string primed into the same prompt. Your dictionary is merged ahead of it, so both take effect together. Useinitial_promptfor a sentence of context ("A talk about Kubernetes and GitOps"); use the dictionary for individual terms. Theyazses tunelearning loop proposes additions toinitial_promptfrom your corpus. -
The
hotwordsfeature ([hotwords], off by default) goes further than a soft prompt: it biases recognition toward your vocabulary with a hotword trie, so rare names and jargon actually win the decode rather than just being hinted. Turn it on when a soft prompt isn't enough:
hotwords reads the same personal dictionary you build with yazses vocab, so there is nothing extra to configure — enable it and your existing words get the stronger biasing.