Allow visualizing VAD
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b036dc2f68
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@ -16,18 +16,31 @@ import numpy as np
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import sounddevice as sd
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import websockets
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# Desired audio properties
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TARGET_SAMPLE_RATE = 24000
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TARGET_CHANNELS = 1 # Mono
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SAMPLE_RATE = 24000
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# The VAD has several prediction heads, each of which tries to determine whether there
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# has been a pause of a given length. The lengths are 0.5, 1.0, 2.0, and 3.0 seconds.
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# Lower indices predict pauses more aggressively. In Unmute, we use 2.0 seconds = index 2.
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PAUSE_PREDICTION_HEAD_INDEX = 2
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async def receive_messages(websocket):
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async def receive_messages(websocket, show_vad: bool = False):
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"""Receive and process messages from the WebSocket server."""
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try:
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speech_started = False
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async for message in websocket:
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data = msgpack.unpackb(message, raw=False)
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if data["type"] == "Word":
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# The Step message only gets sent if the model has semantic VAD available
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if data["type"] == "Step" and show_vad:
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pause_prediction = data["prs"][PAUSE_PREDICTION_HEAD_INDEX]
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if pause_prediction > 0.5 and speech_started:
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print("| ", end="", flush=True)
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speech_started = False
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elif data["type"] == "Word":
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print(data["text"], end=" ", flush=True)
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speech_started = True
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except websockets.ConnectionClosed:
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print("Connection closed while receiving messages.")
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@ -38,17 +51,20 @@ async def send_messages(websocket, audio_queue):
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# Start by draining the queue to avoid lags
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while not audio_queue.empty():
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await audio_queue.get()
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print("Starting the transcription")
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while True:
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audio_data = await audio_queue.get()
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chunk = {"type": "Audio", "pcm": [float(x) for x in audio_data]}
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msg = msgpack.packb(chunk, use_bin_type=True, use_single_float=True)
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await websocket.send(msg)
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except websockets.ConnectionClosed:
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print("Connection closed while sending messages.")
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async def stream_audio(url: str, api_key: str):
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async def stream_audio(url: str, api_key: str, show_vad: bool):
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"""Stream audio data to a WebSocket server."""
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print("Starting microphone recording...")
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print("Press Ctrl+C to stop recording")
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@ -63,8 +79,8 @@ async def stream_audio(url: str, api_key: str):
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# Start audio stream
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with sd.InputStream(
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samplerate=TARGET_SAMPLE_RATE,
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channels=TARGET_CHANNELS,
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samplerate=SAMPLE_RATE,
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channels=1,
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dtype="float32",
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callback=audio_callback,
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blocksize=1920, # 80ms blocks
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@ -73,7 +89,9 @@ async def stream_audio(url: str, api_key: str):
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# Instead of using the header, you can authenticate by adding `?auth_id={api_key}` to the URL
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async with websockets.connect(url, additional_headers=headers) as websocket:
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send_task = asyncio.create_task(send_messages(websocket, audio_queue))
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receive_task = asyncio.create_task(receive_messages(websocket))
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receive_task = asyncio.create_task(
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receive_messages(websocket, show_vad=show_vad)
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)
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await asyncio.gather(send_task, receive_task)
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@ -91,11 +109,16 @@ if __name__ == "__main__":
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parser.add_argument(
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"--device", type=int, help="Input device ID (use --list-devices to see options)"
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)
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parser.add_argument(
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"--show-vad",
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action="store_true",
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help="Visualize the predictions of the semantic voice activity detector with a '|' symbol",
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)
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args = parser.parse_args()
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def handle_sigint(signum, frame):
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print("Interrupted by user")
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print("Interrupted by user") # Don't complain about KeyboardInterrupt
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exit(0)
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signal.signal(signal.SIGINT, handle_sigint)
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@ -109,4 +132,4 @@ if __name__ == "__main__":
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sd.default.device[0] = args.device # Set input device
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url = f"{args.url}/api/asr-streaming"
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asyncio.run(stream_audio(url, args.api_key))
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asyncio.run(stream_audio(url, args.api_key, args.show_vad))
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