Update the card from the 3.3.2 release

README.md

@@ -25,11 +25,11 @@ A speech-to-text model for mobiles, wearables, robots, smart home, automotive an
 
 Whistle does three jobs, all of them on the device:
 
-- **Transcription**: 16 kHz mono audio of any length, one pass up to 30 seconds and windowed beyond it, in English, German, French, Spanish, Italian, Dutch and Polish. The language is detected unless you name it, and silence returns an empty transcript rather than an invented sentence. Live audio streams for as long as you like, committing the words two passes agree on.
+- **Transcription**: 16 kHz mono audio of any length, one pass up to 30 seconds and windowed beyond it, in English, German, French, Spanish, Italian, Dutch and Polish. The language is detected unless you name it, and silence and steady noise return an empty transcript rather than an invented sentence; other sounds, music especially, can still come out as text, so put a voice activity detector or a wake word in front of an always-on microphone. Live audio streams for as long as you like, committing the words two passes agree on.
 - **Word timestamps**: every word with its start, end and probability, aligned from the decoder's own attention, so an app can highlight, seek or cut on a word.
 - **Speech embedding**: the encoder output, one row per 80 ms frame, for matching and retrieval without decoding a transcript at all.
 
-Keyword biasing takes the names, places and product words your users actually say and favours them during the search, so the ones that matter survive.
+Keyword biasing takes the names, places, product words and jargon your users actually say and favours them during the search, so the ones that matter survive.
 
 ## Model