Tune for speed and accuracy¶

YazSes runs entirely on your CPU with no cloud. The main trade-off is model size vs. latency: bigger models are more accurate but take longer to decode. This guide covers the knobs that matter — the STT model, the microphone gate, and CPU-load handling.

Choose the STT model¶

The transcription model is set in config.toml under [stt]:

[stt]
model = "base.en"       # default — good accuracy/latency balance
device = "cpu"
compute_type = "int8"   # 8-bit quantization keeps CPU decode fast

Guidance:

• Start on base.en. Only drop to tiny.en if decode latency is genuinely painful — it produces noticeably more word errors.
• Move up to small.en when accuracy matters more than the extra decode time.
• The .en (English-only) variants are faster and more accurate for English than the multilingual models of the same size; use a multilingual model only if you dictate in other languages.
• compute_type = "int8" is the fast default. int8_float16 or float16 can be slightly more accurate on capable hardware; float32 is slowest.
• device = "cpu" is the tested path. YazSes is designed for CPU int8; GPU is not the supported default.

Downloading a model: faster-whisper fetches the model automatically the first time the daemon starts with it configured, caching it in the Hugging Face cache. Check whether the configured model is present with:

yazses doctor

which reports the STT model as cached, local, or not yet downloaded. Restart the daemon after changing the model:

yazses restart

Set the microphone gate (VAD threshold)¶

If dictation logs Silent audio -- discarding, your speech is falling below the voice-activity threshold and being dropped. If spurious transcripts appear when you are silent, room noise is above it. Calibrate the threshold to your voice and room:

yazses mic-level              # measure and recommend a threshold
yazses mic-level --set        # measure and write it to config.toml
yazses mic-level -s 6         # record for 6 seconds instead of 4

Speak in a normal voice for the whole countdown. --set writes the recommended value to [accessibility] vad_threshold (default 0.01). Lower it for quiet speech; raise it if background noise triggers false transcripts.

yazses doctor --mic records a short ambient clip and warns when the room level already meets or exceeds your threshold (which would cause spurious triggers).

Manage CPU load¶

Two features help when the CPU is busy — both are off by default:

• Adaptive Latency Governor (latency) — keeps dictation responsive when your CPU is loaded and lets it run faster when the machine is idle, by adapting decode behaviour to current load ([latency] high_load = 85.0, low_load = 40.0):

yazses features enable latency
yazses restart

• Ghost Ahead (ghost-ahead) — pre-warms the decoder so the first word comes out slightly faster (it eagerly decodes the buffer when it detects you've stopped; the authoritative transcript still happens on hold-release). Config lives under [endpoint] (prewarm = true):

yazses features enable ghost-ahead
yazses restart

Let the learning loop tune for you¶

If you opt into the local, encrypted learning corpus ([learning] enabled), the yazses tune command analyses your dictation history and proposes concrete config diffs — vocabulary additions, a better VAD threshold, even a model change — that you approve before they are written. Everything stays on your machine.

yazses tune            # propose changes
yazses tune --apply    # write the approved changes

See also¶

• Configuration reference — [stt], [accessibility], [endpoint], [latency]
• Feature reference
• Add words to your personal dictionary — the other half of accuracy.