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felixmandClaude Opus 5 e3faf32f55 Fix Linux capture: negotiate rate, condition audio, pin the device

Transcripts were far worse on Linux than on Windows for the same model, because
of what reached the API rather than the model itself.

Picking any mic from the tray menu never worked: PortAudio exposes the friendly
names through PipeWire's JACK host API, which only accepts 48 kHz, so opening at
16 kHz failed outright and recording always fell back to the system default —
whichever source PipeWire happened to prefer at that moment. That source is
often the raw AMD digital mic, which ships a +0.14 FS DC bias, a full-scale
clipped click in the first 15 ms of every stream, and speech around -50 dBFS.
Windows' vendor driver hides all of this; PipeWire hands over the raw stream.

- Negotiate rate and channels per device, then downmix and resample with
  resample_poly, so every listed device can actually be recorded from.
- Hide devices that cannot work: playback endpoints JACK re-exposes as inputs,
  and raw ALSA hw: devices a sound server already owns (acp: hw:2,0 blocks
  forever on open).
- Persist the chosen device by name in device.txt; PortAudio indices shift as
  USB gear comes and goes. Add a "System default" menu entry.
- Condition every clip before upload: trim the warm-up click, high-pass out DC,
  normalise towards -20 dBFS under a -1 dBFS ceiling.
- Refuse near-silent clips instead of paying for a hallucination, and log
  capture levels (speech, rms, peak, DC, clipping) plus PortAudio status
  warnings, which previously went to a discarded stderr.
- Import scipy.signal as dsp: it was shadowing the stdlib signal module that
  the SIGUSR1 hotkey toggle depends on.

mic_check.py records from Blurt's configured input, reports levels before and
after conditioning, saves the WAV, and transcribes it with the current model.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

2026-08-18 18:58:39 -04:00

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Blurt

Tray-based push-to-talk voice-to-text for Linux and Windows. Toggle recording with a hotkey, speak, toggle off — Blurt transcribes the clip and copies the text to your clipboard.

If a transcript starts with to my agent, the rest is dispatched as an agent task instead of copied.

Setup

Requires uv and Python 3.11+.

uv sync

API key

Blurt reads the key for its current model's provider in this order: environment variable → OS keyring → local file.

Provider	Env var	Keyring (`service` / `user`)	File
OpenAI	`OPENAI_API_KEY`	`openai-api-key` / `felixm`	`api_key.txt`
OpenRouter	`OPENROUTER_API_KEY`	`openrouter-api-key` / `felixm`	`openrouter_key.txt`

Key files and runtime config stay local (gitignored).

Running

Linux — uv run blurt starts the tray icon. Bind a hotkey to ./blurt-toggle, which signals the running instance to start/stop recording.

Windows — launch blurt.vbs (runs Blurt with no console window). The global hotkey is F20.

Configuration

Set from the tray menu, or via files / env vars:

Model — model.txt / BLURT_TRANSCRIPTION_MODEL. For lowest latency use openai/whisper-large-v3-turbo (OpenRouter, served by Groq).
Language — language.txt / BLURT_TRANSCRIPTION_LANGUAGE (en, de).
Input device — tray menu (persisted by name in device.txt / BLURT_INPUT_DEVICE). Pick an explicit mic: PortAudio device indices shift when USB gear comes and goes, and the OS default source can change under you. The menu hides playback endpoints and raw ALSA hw: devices that the sound server already owns; BLURT_INPUT_DEVICE can still name one directly. Devices that refuse 16 kHz (raw ALSA and PipeWire's JACK endpoints do) are captured at their native rate and resampled.

Every clip is conditioned before upload — the first 150 ms are dropped (mics click when the stream opens), DC bias is filtered out, and the level is normalised towards -20 dBFS. Near-silent clips are refused instead of being sent, since transcription models answer silence with confident hallucinations.

Checking the microphone

uv run mic_check.py [device] [seconds] records from Blurt's configured input, prints levels before and after conditioning, saves the WAV it would have uploaded, and transcribes it with the current model. Use it when transcripts come back wrong: bad audio shows up as a DC bias, clipping, or a speech level far below -30 dBFS.

Logs are written to blurt.log in your temp directory (openable from the tray menu).

Moving to another machine

uv run export.py writes a zip of just the source (no 200 MB+ .venv, no caches, no key files) to your temp directory. It's pure Python, so it runs the same on Linux and Windows — no shell needed — and it only reads, so it's safe while Blurt is recording. Unzip on the other machine and uv sync to rebuild .venv for that OS. (Or simply git clone the repo fresh.)

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