remove rhasspy bits
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# Configuration for using Open Wake Work with Rhasspy voice assistant
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# MQTT broker config
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# If running Rhasspy in Docker you'll need to run your own MQTT broker
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# and set Rhasspy MQTT to `external`.
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mqtt:
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broker: 127.0.0.1
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port: 1883
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username: mymqttusername # Login to broker. Delete if not required
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password: mymqttpassword # Login to broker. Delete if not required
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# Open Wake Word config
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oww:
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model_names: # From https://github.com/dscripka/openWakeWord/blob/main/openwakeword/__init__.py
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- alexa # Delete to ignore this wake-word
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- hey_mycroft
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- hey_jarvis
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- timer
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- weather
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activation_samples: 3 # Number of samples in moving average
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activation_threshold: 0.7 # Trigger wakeword when average above this threshold
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deactivation_threshold: 0.2 # Do not trigger again until average falls below this threshold
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# OWW config, see https://github.com/dscripka/openWakeWord#recommendations-for-usage
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vad_threshold: 0.5
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enable_speex_noise_suppression: false
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# Rhasspy microphone UDP ports, 1 per device/satellite
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# https://rhasspy.readthedocs.io/en/latest/tutorials/#udp-audio-streaming
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udp_ports:
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base: 12202 # Delete or change as needed
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kitchen: 12203 # Delete or change as needed
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bedroom: 12204 # Delete or change as needed
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207
detect.py
207
detect.py
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"""
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Listen on UDP for audio from Rhasspy, detect wake words using Open Wake Word,
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and publish on MQTT when wake word is detected to trigger Rhasspy speech-to-text.
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"""
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import argparse
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import io
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import queue
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import socket
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import threading
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import time
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import wave
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from collections import deque
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from json import dumps
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import numpy as np
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import paho.mqtt.client
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import yaml
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from openwakeword.model import Model
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RHASSPY_BYTES = 2092
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RHASSPY_FRAMES = 1024
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OWW_FRAMES = 1280 # 80 ms window @ 16 kHz = 1280 frames
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parser = argparse.ArgumentParser(description="Open Wake Word detection for Rhasspy")
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parser.add_argument(
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"-c",
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"--config",
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default="config.yaml",
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help="Configuration yaml file, defaults to `config.yaml`",
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dest="config_file",
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)
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args = parser.parse_args()
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def load_config(config_file):
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"""Use config.yaml to override the default configuration."""
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try:
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with open(config_file, "r") as f:
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config_override = yaml.safe_load(f)
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except FileNotFoundError:
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config_override = {}
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default_config = {
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"mqtt": {
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"broker": "127.0.0.1",
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"port": 1883,
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"username": None,
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"password": None,
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},
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"oww": {
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"model_names": ["alexa", "hey_mycroft", "hey_jarvis", "timer", "weather"],
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"activation_threshold": 0.7,
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"deactivation_threshold": 0.2,
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"activation_samples": 3,
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"vad_threshold": 0,
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"enable_speex_noise_suppression": False,
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},
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"udp_ports": {"base": 12202},
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}
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config = {**default_config, **config_override}
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if not config["udp_ports"]:
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print(
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"No UDP ports configured. Configure UDP ports to receive audio for wakeword detection."
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)
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exit()
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return config
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class RhasspyUdpAudio(threading.Thread):
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"""Get audio from UDP stream and add to wake word detection queue."""
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def __init__(self, roomname, port, queue):
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threading.Thread.__init__(self)
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self.roomname = roomname
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self.port = port
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self.queue = queue
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self.buffer = []
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self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
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self.sock.bind(("", port))
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def run(self):
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"""Thread to receive UDP audio and add to processing queue."""
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print(f"Listening for {self.roomname} audio on UDP port {self.port}")
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while True:
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data, addr = self.sock.recvfrom(RHASSPY_BYTES)
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audio = wave.open(io.BytesIO(data))
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frames = audio.readframes(RHASSPY_FRAMES)
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self.buffer.extend(np.frombuffer(frames, dtype=np.int16))
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if len(self.buffer) > OWW_FRAMES:
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self.queue.put(
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(
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self.roomname,
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time.time(),
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np.asarray(self.buffer[:OWW_FRAMES], dtype=np.int16),
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)
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)
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self.buffer = self.buffer[OWW_FRAMES:]
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class Prediction(threading.Thread):
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"""Process wake word detection queue and publishing MQTT message when a wake word is detected."""
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def __init__(self, queue):
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threading.Thread.__init__(self)
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self.queue = queue
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self.filters = {}
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self.mqtt = paho.mqtt.client.Client()
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self.mqtt.username_pw_set(
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config["mqtt"]["username"], config["mqtt"]["password"]
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)
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self.mqtt.connect(config["mqtt"]["broker"], config["mqtt"]["port"], 60)
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self.mqtt.loop_start()
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print("MQTT: Connected to broker")
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self.oww = Model(
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# wakeword_model_names=["hey_mycroft", "dog"],
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vad_threshold=config["oww"]["vad_threshold"],
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enable_speex_noise_suppression=config["oww"][
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"enable_speex_noise_suppression"
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],
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)
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def run(self):
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"""
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Wake word detection thread.
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Detect and filter all wake-words, but only publish to MQTT if wake-word model name is listed
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in config.yaml.
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"""
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while True:
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roomname, timestamp, audio = self.queue.get()
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prediction = self.oww.predict(audio)
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for wakeword in prediction.keys():
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confidence = prediction[wakeword]
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if (
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self.__filter(wakeword, confidence)
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and wakeword in config["oww"]["model_names"]
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):
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self.__publish(wakeword, roomname)
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def __filter(self, wakeword, confidence):
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"""
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Filter so that a wakeword is only triggered once per utterance.
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When simple moving average (of length `activation_samples`) crosses the `activation_threshold`
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for the first time, then trigger Rhasspy. Only "re-arm" the wakeword when the moving average
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drops below the `deactivation_threshold`.
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"""
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try:
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self.filters[wakeword]["samples"].append(confidence)
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except KeyError:
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self.filters[wakeword] = {
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"samples": deque(
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[confidence], maxlen=config["oww"]["activation_samples"]
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),
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"active": False,
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}
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moving_average = np.average(self.filters[wakeword]["samples"])
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activated = False
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if (
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not self.filters[wakeword]["active"]
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and moving_average >= config["oww"]["activation_threshold"]
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):
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self.filters[wakeword]["active"] = True
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activated = True
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elif (
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self.filters[wakeword]["active"]
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and moving_average < config["oww"]["deactivation_threshold"]
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):
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self.filters[wakeword]["active"] = False
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if moving_average > 0.1:
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print(f"{wakeword:<16} {activated!s:<8} {self.filters[wakeword]}")
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return activated
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def __publish(self, wakeword, roomname):
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"""Publish wake word message to Rhasspy Hermes/MQTT."""
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payload = {
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"modelId": wakeword,
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"modelVersion": "",
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"modelType": "universal",
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"currentSensitivity": config["oww"]["activation_threshold"],
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"siteId": roomname,
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"sessionId": None,
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"sendAudioCaptured": None,
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"lang": None,
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"customEntities": None,
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}
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self.mqtt.publish(f"hermes/hotword/{wakeword}/detected", dumps(payload))
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print(f"MQTT: Published wakeword {wakeword}, siteId {roomname} to Rhasspy")
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if __name__ == "__main__":
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config = load_config(args.config_file)
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q = queue.Queue()
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threads = []
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for roomname, port in config["udp_ports"].items():
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t = RhasspyUdpAudio(roomname, port, q)
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t.daemon = True
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t.start()
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threads.append(t)
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t = Prediction(q)
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t.start()
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threads.append(t)
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print(f"Threads: {threads}")
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