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import os,argparse
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import traceback
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from tqdm import tqdm
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path_denoise = 'tools/denoise-model/speech_frcrn_ans_cirm_16k'
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path_denoise = path_denoise if os.path.exists(path_denoise) else "damo/speech_frcrn_ans_cirm_16k"
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ans = pipeline(Tasks.acoustic_noise_suppression,model=path_denoise)
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def execute_denoise(input_folder,output_folder):
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os.makedirs(output_folder,exist_ok=True)
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for name in tqdm(os.listdir(input_folder)):
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try:
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ans("%s/%s"%(input_folder,name),output_path='%s/%s'%(output_folder,name))
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except:
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traceback.print_exc()
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument("-i", "--input_folder", type=str, required=True,
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help="Path to the folder containing WAV files.")
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parser.add_argument("-o", "--output_folder", type=str, required=True,
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help="Output folder to store transcriptions.")
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parser.add_argument("-p", "--precision", type=str, default='float16', choices=['float16','float32'],
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help="fp16 or fp32")
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cmd = parser.parse_args()
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execute_denoise(
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input_folder = cmd.input_folder,
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output_folder = cmd.output_folder,
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) |
