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34 lines
986 B
Python
34 lines
986 B
Python
import openai
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import whisper
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import os
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import torch
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def get_model(use_api):
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if use_api:
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return APIWhisperTranscriber()
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else:
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return WhisperTranscriber()
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class WhisperTranscriber:
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def __init__(self):
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self.audio_model = whisper.load_model(os.path.join(os.getcwd(), 'tiny.en.pt'))
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print(f"[INFO] Whisper using GPU: " + str(torch.cuda.is_available()))
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def get_transcription(self, wav_file_path):
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try:
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result = self.audio_model.transcribe(wav_file_path, fp16=torch.cuda.is_available())
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except Exception as e:
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print(e)
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return ''
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return result['text'].strip()
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class APIWhisperTranscriber:
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def get_transcription(self, wav_file_path):
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audio_file= open(wav_file_path, "rb")
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try:
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result = openai.Audio.translate("whisper-1", audio_file)
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except Exception as e:
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print(e)
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return ''
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return result['text'].strip() |