Lorre

Lorre is a macOS transcription workspace for capturing or importing audio, processing it locally, reviewing speaker-labeled transcript segments, and exporting the result in multiple formats.

Key features

• Capture any conversation your way with Microphone, System audio, or Microphone + system audio.
• See live transcription as you record, including mixed mic + system audio sessions.
• Powered by Parakeet TDT 0.6B v3, a fast multilingual ASR model that runs on Apple's Neural Engine and automatically transcribes 25 European languages right on your Mac.
• Supports automatic language detection across 25 European languages, including Dutch, English, German, French, Spanish, and more.
• Built on FluidAudio for local speech recognition, voice activity detection, and speaker diarization.
• Keep your recordings and transcripts on your Mac for a private local workflow.
• Enable Privacy Mode to automatically delete source audio after the transcript is saved.
• Import existing audio files and run them through the same transcription pipeline.
• Review transcripts with speaker labels, playback, speaker reassignment, and inline text editing.
• Export finished sessions as Markdown, plain text, or JSON.

What is FluidAudio?

FluidAudio is the on-device speech engine behind Lorre. It is a Swift library for Apple devices that combines speech-to-text, voice activity detection, and speaker diarization in one local pipeline.

Lorre uses FluidAudio's Parakeet TDT 0.6B v3 model for final transcription. In simple terms, Parakeet is the ASR model that listens to your recording and turns spoken words into text. It supports automatic language detection across 25 European languages, while Lorre can use FluidAudio's faster streaming models to show a live preview while you are still recording.

ANE-optimized means FluidAudio is tuned to run efficiently on Apple's Neural Engine, the part of Apple silicon designed for AI workloads. For a user, that usually means faster transcription, lower power use, and less pressure on the CPU and GPU.

Parakeet 0.6B means the model has about 600 million parameters. That is relatively compact compared with many modern AI models, which helps keep it practical for local use on a Mac without needing the kind of memory larger cloud-style models often expect.

The main benefit of FluidAudio is that it gives Lorre a complete local speech stack:

• your audio can stay on your Mac instead of being sent to a cloud API
• it is built for Apple devices, so it can take advantage of Apple hardware for speed and efficiency
• it handles the hard parts together: detecting speech, transcribing it, and separating speakers

That is what lets Lorre offer private, on-device transcription with speaker labeling in a single app.

Requirements

• macOS 14 or later
• Microphone access for microphone recording
• Screen and System Audio Recording access for system-audio capture
• A local build environment for Swift if you want to run from source

Build and run

swift run

To build the app bundle in dist/:

./scripts/package_macos_app.sh

Privacy and local data

Lorre stores session data in ~/Library/Application Support/Lorre/.

Each session is kept in its own folder and can contain:

• session.json for session metadata
• transcript.json for transcript data
• recorded or imported audio
• optional microphone and system-audio stem files for mixed recordings
• exported transcript files

If privacy mode is enabled before a recording or import, Lorre deletes the source audio after transcription completes and keeps the transcript and exports.

Export formats

• Markdown
• Plain text
• JSON