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