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mlx-whisper real time audio
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# Required packages: | |
# pip install SpeechRecognition mlx-whisper pyaudio | |
# Note: This script requires Apple Silicon Mac for MLX Whisper | |
import speech_recognition as sr | |
import numpy as np | |
import mlx_whisper | |
r = sr.Recognizer() | |
mic = sr.Microphone(sample_rate=16000) | |
print("Listening...") | |
try: | |
with mic as source: | |
r.adjust_for_ambient_noise(source) | |
while True: | |
audio = r.listen(source) | |
# Convert audio to numpy array | |
audio_data = np.frombuffer(audio.get_raw_data(), dtype=np.int16).astype(np.float32) / 32768.0 | |
# Process audio with Apple MLXWhisper model | |
result = mlx_whisper.transcribe(audio_data, path_or_hf_repo="mlx-community/whisper-large-v3-turbo")["text"] | |
# Print the transcribed text | |
print(result) | |
except KeyboardInterrupt: | |
print("Stopped listening.") | |
seems this is a prerequisite:
brew install portaudio
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Suggestion: you can use an inline script dependencies block and then run it with
uv run
- see my fork https://gist.github.com/simonw/57f9c15bbd9d484f762058f83412aefb