surface to pick which
one listens.
Detection runs entirely on-device. The always-on listener only watches for
the wake phrase; no audio leaves your machine until you actually speak a command
to the agent.
How it works
- With
wake_word.enabled: true(or after/wake on), a lightweight hotword detector listens on your configured input device, or the process default microphone whenwake_word.input_deviceis unset. - When it hears the wake phrase it pauses itself (freeing the mic), starts a new session, and records one utterance with voice mode’s silence detection.
- Your speech is transcribed and sent to the agent. After it replies, the listener resumes automatically and waits for the next wake word.
Remote desktop (client capture)
When the desktop app connects to a remote Mibyan backend (for example a headless Docker host or a machine in another room), the backend often has no microphone. Server-side PortAudio then fails with “Failed to open the wake-word microphone.” Mibyan supports client capture for that case:- The desktop arms wake with
capture: client(automatic for the GUI when the backend has no local input device, or set explicitly below). - The selected wake engine still runs on the backend (same engines, same models).
- The desktop opens the local Mac/PC microphone, resamples to 16 kHz mono
int16, and streams short frames via the
wake.feedRPC. - On detection the backend emits
wake.detectedas usual; the desktop starts the normal voice pipeline on the client mic.
client_capture: true on wake.start, so remote
backends without a mic arm in client mode automatically. CLI and TUI keep local
capture unless you set capture: client explicitly.
Privacy note: with client capture, wake PCM travels over the authenticated
desktop↔backend WebSocket (same channel as the rest of the session). Detection
still does not send audio to third-party wake APIs; the engine is local to the
backend process.
Engines
The default provider is
auto. It selects the first platform-supported
engine in this order: openWakeWord → sherpa → Porcupine. The platform is
that of the Python backend, not a remote desktop client:
- Native Windows ARM64 and Intel macOS: sherpa (free, no key).
- Windows x64, Apple Silicon, and supported Linux targets: openWakeWord (free, no key).
mibyan config set wake_word.provider auto. Wake detection stays off
until you enable it.
The default phrase label is “hey mibyan”. For openWakeWord, Mibyan includes
its trained TFLite model.
The pyopen-wakeword package includes the shared feature-extraction models, so
this engine does not download models when it starts.
If the selected engine is missing, Mibyan requests its PM extra when you enable
wake-word detection. security.allow_lazy_installs controls this installation.
A new dependency environment can require a Mibyan restart before the engine loads.
Packaged builds include the engine dependencies supported by their target.
The pyopen-wakeword macOS
wheel contains an ARM64-only library despite its universal2 label. Mibyan
excludes that engine on Intel Macs and native Windows ARM64. Sherpa provides
keyless detection on both targets.
Porcupine’s default keyword is “jarvis”, not “hey mibyan”. Its phrase
setting is only a display label; choose a built-in keyword or supply a custom
.ppn model to change what it detects. Get an access key at
console.picovoice.ai and store
PORCUPINE_ACCESS_KEY in your profile’s .env, not config.yaml.
The supported pyopen-wakeword wheels target Apple Silicon with macOS 15 or
later, glibc Linux 2.35 or later, and Windows x64. These requirements apply to
that engine, not every Mibyan feature. Termux’s core/ACP package does not
include this wake stack.
Quick start
/wake or the
desktop ear button — also writes wake_word.enabled to ~/.mibyan/config.yaml,
so your choice persists across sessions. You can also flip it by hand:
Configuration
sensitivity and start_new_session apply to all three engines. For sherpa,
phrase selects the detection phrase. For openWakeWord and Porcupine, phrase
is a display label; their model or keyword selects the detection phrase.
input_device is passed directly to the wake listener’s PortAudio
(sounddevice) stream. Use either a numeric device index or an unambiguous
device-name substring. This setting only changes wake-word capture; desktop
push-to-talk still uses the desktop application’s microphone path.
Reducing false triggers on ambient speech
openWakeWord scores one short (~80ms) audio frame at a time, so a stray phoneme in background conversation can occasionally spike a single frame over the threshold and fire the wake word unintentionally. Two knobs control this:confirmation_frames(default3, openWakeWord only) — how many consecutive over-threshold frames are required before the wake fires. A real “hey mibyan” holds a high score across several frames; an ambient blip spikes just one. Raise it (e.g.4–5) if you still get false triggers in a noisy room; the cost is a few tens of milliseconds of extra latency.1restores the old fire-on-first-frame behavior.sensitivity(default0.6) — the detection threshold,0.0–1.0. Higher is stricter (fewer false triggers). This direction is consistent across all engines — for openWakeWord it’s the raw per-frame score threshold, for sherpa it maps onto the keyword threshold, and for Porcupine it’s inverted internally so “higher = stricter” holds there too. The0.6default sits above openWakeWord’s permissive0.5baseline, which let near-misses like “hey hor” through; raise toward0.8if you still get false fires, lower it if real “hey mibyan” utterances are missed.
sherpa and porcupine engines decode the whole phrase internally, so they
don’t have the single-frame-spike problem and ignore confirmation_frames
(but they still honor sensitivity).
The openwakeword provider name now selects
pyopen-wakeword. Its wheel includes
the TFLite library and shared feature models. Mibyan uses the bundled
hey_mibyan.tflite model by default. ONNX wake models and the
inference_framework setting are no longer supported.
Surfaces (CLI, TUI, GUI)
The wake word works in all three Mibyan surfaces, andsurface picks which one
owns the listener and opens the new session when it fires:
The detector is on-device and single-mic, so only one surface listens at a time,
including when Mibyan surfaces run in separate processes. Ownership is sticky:
the first eligible claimant keeps the listener until it stops, disconnects, or
its process exits. Mibyan does not silently fail over to another open surface.
Set
surface when you want to pin ownership instead of using first-claim wins.
The TUI and desktop GUI share the same Python backend (tui_gateway), which
runs the detector server-side and yields the mic to voice capture while a
command records.
Using a different phrase
“Hey Mibyan” is the default detection phrase with openWakeWord and sherpa. Porcupine uses its configured keyword instead (“jarvis” by default). To wake on something else, the easiest path on supported platforms is the open-vocabulary engine:Option A — sherpa (any phrase, zero training)
Type the phrase you want; it’s tokenized at runtime — “hey coder”, “computer”, “wake up neo”, anything:Waking a specific profile (desktop)
With the sherpa engine, ONE listener can wake ANY profile. Every profile whose config haswake_word.enabled: true is enrolled automatically; its
phrase defaults to hey <profile name> when unset. Say a profile’s phrase
and the desktop app live-switches to that profile, opens a fresh session
there, and starts hands-free voice:
- “hey mibyan” → default profile
- “hey coder” → the
coderprofile - “hey trader” → the
traderprofile
wake_word.profile_routing: false on the listener’s profile to opt out
and listen only for its own phrase. The CLI and TUI are single-profile
processes: a wake phrase belonging to another profile prints the switch
command (mibyan -p <profile>) instead of routing.
Names are matched acoustically by their English subword sounds: two-word
phrases with distinct, 2+ syllable names work best. Very short names, heavy
non-English phonology, or two profiles with similar-sounding names will
degrade accuracy — tune per-profile sensitivity if needed.
Option B — openWakeWord (free, trained model)
For a different phrase, obtain or train a compatible openWakeWord TFLite model. Set its absolute path in the configuration. Mibyan does not resolve built-in names such ashey_jarvis or download their models for you.
Option C — Porcupine (custom keyword in seconds)
Create a “Hey Mibyan” keyword in the Picovoice Console, download the.ppn, and:
~/.mibyan/.env:
Requirements
- A working microphone and the
sounddevice+numpyaudio stack (shared with voice mode). - An STT provider for transcribing the spoken command — local
faster-whisperworks out of the box; see Voice Mode for the full provider list. - A TTS provider for speaking the reply (the default
edge-ttsworks with no key). The wake flow is fully hands-free, so the toggle refuses to arm until both STT and TTS are ready —mibyan tools(Voice section) sets them up. - The wake engine deps (auto-installed, or
mibyan-agent[wake]).
/wake status reports exactly what’s missing if the listener won’t start.
”Listening” but never wakes (macOS)
macOS grants microphone access per process. STT working in the desktop app proves the renderer has mic access — the wake listener runs in the Python backend, which needs its own grant. Without it, CoreAudio hands the backend a “working” stream that only ever delivers silence, so the ear shows listening but the phrase never fires. Mibyan detects this (/wake status shows
“mic delivers only silence”; the desktop’s folded voice menu carries the same
hint on its trigger).
Fix: System Settings → Privacy & Security → Microphone → enable the Mibyan
backend (it may appear as your terminal, python, or Mibyan), then toggle the
wake word off and on.
”Listening” but receives silence (Windows)
Desktop push-to-talk and wake-word capture use different microphone paths. Push-to-talk uses the desktop application’s browser capture, while the wake-word listener opens a PortAudio stream in the Python backend. One can work while the other selects a silent or unusable Windows input./wake status reports the selected input device and Windows audio host API.
When it reports silence, set wake_word.input_device to the numeric index or an
unambiguous name of the working PortAudio input, then toggle the wake word:
null to return to the process default:
Notes & limits
- Local surfaces only. The wake word runs in the CLI, TUI, and desktop GUI — wherever a local microphone is available. It does not run in the messaging gateway (Telegram, Discord, …), which has no mic.
- One mic at a time. The detector releases the microphone while a command is recording and reclaims it once the turn ends, so it won’t fight voice capture.
- Privacy. Hotword detection is local. Set
sensitivityhigher if you get false triggers, lower if it misses you.

