mirror of
https://github.com/w-okada/voice-changer.git
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37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
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import whisper
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import numpy as np
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import torchaudio
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from scipy.io.wavfile import write
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_MODELS = {
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"tiny": "/whisper/tiny.pt",
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"base": "/whisper/base.pt",
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"small": "/whisper/small.pt",
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"medium": "/whisper/medium.pt",
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}
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class Whisper():
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def __init__(self):
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self.storedSizeFromTry = 0
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def loadModel(self, model):
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# self.model = whisper.load_model(_MODELS[model], device="cpu")
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self.model = whisper.load_model(_MODELS[model])
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self.data = np.zeros(1).astype(np.float)
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def addData(self, unpackedData):
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self.data = np.concatenate([self.data, unpackedData], 0)
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def transcribe(self, audio):
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received_data_file = "received_data.wav"
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write(received_data_file, 24000, self.data.astype(np.int16))
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source, sr = torchaudio.load(received_data_file)
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target = torchaudio.functional.resample(source, 24000, 16000)
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result = self.model.transcribe(received_data_file)
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print("WHISPER1:::", result["text"])
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print("WHISPER2:::", result["segments"])
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self.data = np.zeros(1).astype(np.float)
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return result["text"]
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