67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
import whisper
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import numpy as np
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import sounddevice as sd
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import queue
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import sys
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# Parameters
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MODEL_TYPE = "tiny.en"
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CHANNELS = 1
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SAMPLERATE = 16000
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BLOCK_SIZE = 8000 # 0.5 seconds of audio per block
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TRANSCRIBE_RATE = 2 # Process every 2 seconds
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audio_queue = queue.Queue()
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def callback(indata, frames, time, status):
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if status:
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print(status, file=sys.stderr)
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audio_queue.put(indata.copy())
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def main():
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print(f"Loading Whisper model '{MODEL_TYPE}'...")
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model = whisper.load_model(MODEL_TYPE)
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print("Model loaded.")
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print("\nAvailable Audio Devices:")
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devices = sd.query_devices()
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print(devices)
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# Try to find a sensible default if the system one is tricky
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default_device = sd.default.device[0]
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print(f"\nUsing default input device index: {default_device}")
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print("\nStarting live transcription... (Press Ctrl+C to stop)")
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print("Note: On macOS, you may need to grant Microphone permissions to your terminal.\n")
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audio_buffer = np.array([], dtype=np.float32)
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try:
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with sd.InputStream(samplerate=SAMPLERATE, channels=CHANNELS, callback=callback, blocksize=BLOCK_SIZE):
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while True:
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# Pull all available data from the queue
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while not audio_queue.empty():
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data = audio_queue.get()
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audio_buffer = np.append(audio_buffer, data.flatten())
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# If we have enough audio, transcribe it
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if len(audio_buffer) >= SAMPLERATE * TRANSCRIBE_RATE:
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# Transcribe the current buffer
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# fp16=False is used for CPU execution
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result = model.transcribe(audio_buffer, fp16=False, language="en")
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text = result['text'].strip()
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if text:
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print(f"Transcription: {text}")
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# Clear buffer for next chunk
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audio_buffer = np.array([], dtype=np.float32)
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except KeyboardInterrupt:
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print("\nStopped by user.")
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except Exception as e:
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print(f"\nError: {e}")
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if __name__ == "__main__":
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main()
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