eca74772de
Using Hermes MQTT. Wake word is detected multiple times, added debug messages and some timeout code to mitigate multiple activations of Rhasspy. config.yaml for configuration of MQTT and open wake word
134 lines
4 KiB
Python
134 lines
4 KiB
Python
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 json import dumps
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import numpy as np
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import paho.mqtt.client as mqtt
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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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CHUNK = 1280 # 80 ms window @ 16 kHz = 1280 frames
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OWW_FRAMES = CHUNK * 3 # Increase efficiency of detection but higher latency
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q = queue.Queue()
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parser = argparse.ArgumentParser(description="PiJuice to MQTT")
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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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"""Load the configuration from config yaml file and use it to override the defaults."""
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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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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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"activation_threshold": 0.5,
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"vad_threshold": 0,
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"enable_speex_noise_suppression": False,
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},
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}
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config = {**default_config, **config_override}
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return config
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def receive_udp_audio(port=12102):
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"""
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Get audio from UDP stream and add to wake word detection queue.
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Rhasspy sends 1024 x 16bit frames + header = 2092 bytes
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Open Wake Word expects minimum of 1280 x 16bit frames
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"""
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sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
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sock.bind(("", port))
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print(f"Listening on UDP port {port}")
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audio_buffer = []
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while True:
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data, addr = 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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audio_buffer.extend(np.frombuffer(frames, dtype=np.int16))
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print(".", end="", flush=True)
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if len(audio_buffer) > OWW_FRAMES:
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q.put(
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np.asarray(audio_buffer[:OWW_FRAMES], dtype=np.int16)
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) # Must be np array for VAD
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audio_buffer = audio_buffer[OWW_FRAMES:]
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def on_connect(client, userdata, flags, rc):
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client.subscribe("hermes/hotword/#")
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def on_message(client, userdata, msg):
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# print(f"{msg.topic} {msg.payload}")
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pass
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config = load_config(args.config_file)
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if __name__ == "__main__":
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client = mqtt.Client()
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client.on_connect = on_connect
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client.on_message = on_message
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client.username_pw_set(config["mqtt"]["username"], config["mqtt"]["password"])
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client.connect(config["mqtt"]["broker"], config["mqtt"]["port"], 60)
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print("Connected to MQTT broker")
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oww = Model(
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vad_threshold=config["oww"]["vad_threshold"],
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enable_speex_noise_suppression=config["oww"]["enable_speex_noise_suppression"],
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)
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receive_audio_thread = threading.Thread(target=receive_udp_audio)
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receive_audio_thread.start()
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published = 0
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client.loop_start()
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while True:
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prediction = oww.predict(q.get())
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for model_name in prediction.keys():
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prediction_level = prediction[model_name]
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if prediction_level >= config["oww"]["activation_threshold"]:
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delta = time.time() - published
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print(f"{model_name} {prediction_level:.3f} {delta:.3f}")
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if delta > 5:
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payload = {
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"modelId": model_name,
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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": "bedroom",
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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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client.publish(
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f"hermes/hotword/{model_name}/detected", dumps(payload)
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)
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print("Sent wakeword to Rhasspy")
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published = time.time()
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