
Common speech-to-text architectures, explained without the fog
CTC, RNN-T, TDT, Conformer encoders, encoder-decoder Transformers, and the surrounding systems that make local ASR useful.
Muesli field notes
Notes on local ASR, Mac dictation, meeting capture, privacy, model architecture, and the tools that shape how speech becomes part of your workday.

A privacy-first look at medical dictation, clinical scribes, and the local speech-to-text layer doctors can control before notes enter an approved system.
Read the field note18 field notes

CTC, RNN-T, TDT, Conformer encoders, encoder-decoder Transformers, and the surrounding systems that make local ASR useful.

Why Parakeet matters for fast local English ASR, and why a clear sentence from your Mac should not need a cloud round trip.

A practical guide to Whisper’s encoder-decoder design, multilingual strengths, local inference tradeoffs, and where it fits in Muesli.

Why local speech-to-text has advanced far enough that every meeting transcript does not need to begin in someone else’s cloud.

A practical comparison of offline dictation apps for Mac, from built-in Apple Dictation to local model workflows on Apple Silicon.

What changes when your Mac captures the meeting instead of a bot joining Zoom, Meet, or Teams on your behalf.

When built-in voice typing stops being enough: local model choice, transcript history, meeting transcription, and a workflow you control.

ASR, VAD, diarization, neural AEC, CoreML, Apple Neural Engine, Parakeet, Whisper, and the terms behind a local speech stack.

How CoreML and the Apple Neural Engine change the latency, power, and privacy equation for local dictation and transcription.

A practical guide to local voice typing, paste-at-cursor workflows, model choice, privacy, and where Muesli fits.

Capture microphone and system audio from the Mac already in the call, then keep the transcript close before you decide what to share.

What offline means in practice, how local ASR models fit, and why the useful path is still speak, release, and get text where your cursor is.

For people who want Granola-style meeting memory without making a hosted workspace the default home for every transcript.

A practical comparison of polished AI dictation and Muesli’s open-source local-first path for dictation and meeting transcription.

A practical comparison of Wispr Flow alternatives by platform, privacy, offline speech-to-text, open-source software, and the workflows Muesli is built to own.

A Mac-first comparison for people who want meeting capture and local speech-to-text without inviting another participant into every call.

What it looks like when meeting transcription starts on the Mac already in the call instead of with a hosted meeting assistant.
Muesli is open-source Mac dictation and meeting transcription built for local ASR on Apple Silicon.