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import os
import 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,
)
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