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Support multiple wake words

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This commit is contained in:
Michael Hansen
2025-09-15 11:29:28 -05:00
parent 2c937e3cb3
commit e26864a191
4 changed files with 55 additions and 24 deletions
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linux_voice_assistant/__main__.py
+35 -13
View File
@@ -6,7 +6,7 @@ import logging
import threading
from pathlib import Path
from queue import Queue
from typing import Dict
from typing import Dict, List
import sounddevice as sd
@@ -109,16 +109,27 @@ async def main() -> None:
_LOGGER.debug("libtensorflowlite_c path: %s", libtensorflowlite_c_path)
# Load wake/stop models
wake_models: Dict[str, MicroWakeWord] = {}
wake_config_path = wake_word_dir / f"{args.wake_model}.json"
if preferences.active_wake_words:
wake_word_id = preferences.active_wake_words[0]
maybe_wake_config_path = wake_word_dir / f"{wake_word_id}.json"
if maybe_wake_config_path.exists():
# Override with last set
wake_config_path = maybe_wake_config_path
# Load preferred models
for wake_word_id in preferences.active_wake_words:
wake_config_path = wake_word_dir / f"{wake_word_id}.json"
if not wake_config_path.exists():
continue
_LOGGER.debug("Loading wake model: %s", wake_config_path)
wake_model = MicroWakeWord.from_config(wake_config_path, libtensorflowlite_c_path)
_LOGGER.debug("Loading wake model: %s", wake_config_path)
wake_models[wake_word_id] = MicroWakeWord.from_config(
wake_config_path, libtensorflowlite_c_path
)
if not wake_models:
# Load default model
_LOGGER.debug("Loading wake model: %s", wake_config_path)
wake_word_id = wake_config_path.stem
wake_models[wake_word_id] = MicroWakeWord.from_config(
wake_config_path, libtensorflowlite_c_path
)
stop_config_path = wake_word_dir / f"{args.stop_model}.json"
_LOGGER.debug("Loading stop model: %s", stop_config_path)
@@ -130,7 +141,7 @@ async def main() -> None:
audio_queue=Queue(),
entities=[],
available_wake_words=available_wake_words,
wake_word=wake_model,
wake_words=wake_models,
stop_word=stop_model,
music_player=MpvMediaPlayer(device=args.audio_output_device),
tts_player=MpvMediaPlayer(device=args.audio_output_device),
@@ -138,6 +149,7 @@ async def main() -> None:
timer_finished_sound=args.timer_finished_sound,
preferences=preferences,
preferences_path=preferences_path,
libtensorflowlite_c_path=libtensorflowlite_c_path,
)
process_audio_thread = threading.Thread(
@@ -179,6 +191,9 @@ async def main() -> None:
def process_audio(state: ServerState):
"""Process audio chunks from the microphone."""
wake_words: List[MicroWakeWord] = []
try:
while True:
@@ -189,13 +204,20 @@ def process_audio(state: ServerState):
if state.satellite is None:
continue
if (not wake_words) or (state.wake_words_changed and state.wake_words):
# Update list of wake word models to process
state.wake_words_changed = False
wake_words = list(state.wake_words.values())
try:
state.satellite.handle_audio(audio_chunk)
if state.wake_word.is_active and state.wake_word.process_streaming(
audio_chunk
):
state.satellite.wakeup()
for wake_word in wake_words:
if not wake_word.is_active:
continue
if wake_word.process_streaming(audio_chunk):
state.satellite.wakeup(wake_word)
if state.stop_word.is_active and state.stop_word.process_streaming(
audio_chunk
linux_voice_assistant/models.py
+3 -1
View File
@@ -36,7 +36,7 @@ class ServerState:
audio_queue: "Queue[Optional[bytes]]"
entities: "List[ESPHomeEntity]"
available_wake_words: "Dict[str, AvailableWakeWord]"
wake_word: "MicroWakeWord"
wake_words: "Dict[str, MicroWakeWord]"
stop_word: "MicroWakeWord"
music_player: "MpvMediaPlayer"
tts_player: "MpvMediaPlayer"
@@ -44,8 +44,10 @@ class ServerState:
timer_finished_sound: str
preferences: Preferences
preferences_path: Path
libtensorflowlite_c_path: Path
media_player_entity: "Optional[MediaPlayerEntity]" = None
satellite: "Optional[VoiceSatelliteProtocol]" = None
wake_words_changed: bool = False
def save_preferences(self) -> None:
"""Save preferences as JSON."""
linux_voice_assistant/satellite.py
+16 -10
View File
@@ -175,36 +175,42 @@ class VoiceSatelliteProtocol(APIServer):
)
for ww in self.state.available_wake_words.values()
],
active_wake_words=[self.state.wake_word.id],
max_active_wake_words=1,
active_wake_words=list(self.state.wake_words.keys()),
max_active_wake_words=2,
)
_LOGGER.info("Connected to Home Assistant")
elif isinstance(msg, VoiceAssistantSetConfiguration):
# TODO: support multiple wake words
# Change active wake words
active_wake_words: Set[str] = set()
for wake_word_id in msg.active_wake_words:
if wake_word_id == self.state.wake_word.id:
if wake_word_id in self.state.wake_words:
# Already active
active_wake_words.add(wake_word_id)
break
continue
model_info = self.state.available_wake_words.get(wake_word_id)
if not model_info:
continue
_LOGGER.debug("Loading wake word: %s", model_info.config_path)
self.state.wake_word = MicroWakeWord.from_config(
self.state.wake_words[wake_word_id] = MicroWakeWord.from_config(
model_info.config_path,
self.state.wake_word.libtensorflowlite_c_path,
self.state.libtensorflowlite_c_path,
)
_LOGGER.info("Wake word set: %s", self.state.wake_word.wake_word)
_LOGGER.info("Wake word set: %s", wake_word_id)
active_wake_words.add(wake_word_id)
break
for wake_word in self.state.wake_words.values():
wake_word.is_active = wake_word.id in active_wake_words
_LOGGER.debug("Active wake words: %s", active_wake_words)
self.state.preferences.active_wake_words = list(active_wake_words)
self.state.save_preferences()
self.state.wake_words_changed = True
def handle_audio(self, audio_chunk: bytes) -> None:
@@ -213,7 +219,7 @@ class VoiceSatelliteProtocol(APIServer):
self.send_messages([VoiceAssistantAudio(data=audio_chunk)])
def wakeup(self) -> None:
def wakeup(self, wake_word: MicroWakeWord) -> None:
if self._timer_finished:
# Stop timer instead
self._timer_finished = False
@@ -221,7 +227,7 @@ class VoiceSatelliteProtocol(APIServer):
_LOGGER.debug("Stopping timer finished sound")
return
wake_word_phrase = self.state.wake_word.wake_word
wake_word_phrase = wake_word.wake_word
_LOGGER.debug("Detected wake word: %s", wake_word_phrase)
self.send_messages(
[VoiceAssistantRequest(start=True, wake_word_phrase=wake_word_phrase)]