tes
d01b78b225
Plan 3 smoke surfaced 'session_ended reason=error' on every wake with no context. The relay now logs every upstream event type at INFO and forwards any upstream 'error' event to the device as 'error code=upstream_<code>' so it appears in the Pi's journal alongside the wake/session_ended pair. Also extends the client's wakeword.predict with per-frame RMS + score diagnostics and the bridge loop with a 5 s heartbeat for triage.
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
"""openwakeword wrapper for the Pi client.
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Loads the stock `alexa` model. Each call to `predict()` takes a 1280-sample
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16 kHz mono int16 frame (produced by `client.audio.resample_24k_to_16k`).
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Returns True at most once per cooldown window.
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"""
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import time
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import numpy as np
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from client.log import get_logger
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_log = get_logger("wakeword")
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WAKEWORD = "alexa"
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DEFAULT_THRESHOLD = 0.5
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DEFAULT_COOLDOWN_S = 1.5
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class WakewordDetector:
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def __init__(self, *, threshold: float = DEFAULT_THRESHOLD,
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cooldown_s: float = DEFAULT_COOLDOWN_S) -> None:
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# Lazy-import openwakeword to keep the test suite importable without it.
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import openwakeword.utils
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from openwakeword.model import Model
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_log.info("downloading openwakeword models (idempotent)")
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# No-arg form dodges the None-handling crash documented in findings.md §4.
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openwakeword.utils.download_models()
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_log.info("loading openwakeword model %r", WAKEWORD)
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t0 = time.monotonic()
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self._model = Model(wakeword_models=[WAKEWORD], inference_framework="onnx")
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_log.info("openwakeword model loaded in %.2fs", time.monotonic() - t0)
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self._threshold = threshold
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self._cooldown_s = cooldown_s
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self._last_fired = 0.0
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def predict(self, frame_16k_int16: np.ndarray) -> bool:
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scores = self._model.predict(frame_16k_int16)
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score = float(scores.get(WAKEWORD, 0.0))
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rms = float(np.sqrt(np.mean(frame_16k_int16.astype(np.float32) ** 2)))
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now = time.monotonic()
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# Diagnostic: log any non-trivial score so we can see what's getting
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# close to firing.
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if score >= 0.1:
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_log.info("score=%.3f rms=%.0f", score, rms)
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if score >= self._threshold and (now - self._last_fired) >= self._cooldown_s:
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self._last_fired = now
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_log.info("wakeword fired score=%.3f rms=%.0f", score, rms)
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return True
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return False
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