Local Ai
Local dictation for Windows: hold right Ctrl, speak, let go - Ollama does the clean-up
Hold right Ctrl, speak, release. faster-whisper (large-v3-turbo) transcribes on your own GPU, then qwen2.5:3b-instruct through Ollama cleans the text up: filler words out, punctuation in, spoken self-
Hold right Ctrl, speak, release. faster-whisper (large-v3-turbo) transcribes on your own GPU, then qwen2.5:3b-instruct through Ollama cleans the text up: filler words out, punctuation in, spoken self-corrections applied (say "fifty, make that seventy-five" and you get 75). The clean-up model is locked into editing and never answers the text, so a dictated question stays a question. That one constraint is what made it usable every day instead of a toy. Nothing leaves the machine. German and English both work. Numbers on an RTX 2080 Super: a 13-second dictation is transcribed in ~2.3 s, about 5 s end to end no matter how long you talk, because transcription runs while you are still speaking. VRAM: ~1.6 GB for whisper, ~2.1 GB for the clean-up model, keep_alive -1 so there is no cold start on the first dictation. Ollama specifics that cost me time, in case they save you some: keep_alive is ignored on /v1/chat/completions, so the model quietly unloaded after 5 minutes until I switched to the native /api/chat. And 127.0.0.1 instead of localhost, otherwise you eat a 2 s IPv6 timeout on every request. Windows only (pasting and window detection use Windows APIs), slower on CPU, MIT licensed. https://github.com/escape-universe/my-local-whisper submitted by /u/escape_universe [link] [comments]
Related
- Introducing Tap ( Linux Version of Wispr Flow or Aqua )
- I built AmicoScript: A local-first Whisper UI with Speaker Diarization and Ollama integration for summaries.
Source: r/ollama | 2026-09-08