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https://github.com/RVC-Boss/GPT-SoVITS.git
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58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
# -*- coding:utf-8 -*-
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.models import Model
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import multiprocessing
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import sys,os,traceback
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from threading import Lock
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lock = Lock()
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# 进程数
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processes = 2
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dir=sys.argv[1]
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# opt_name=dir.split("\\")[-1].split("/")[-1]
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opt_name=os.path.basename(dir)
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# FunAsr三语转写model
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lang2model = {
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'zh': 'tools/damo_asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch',
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'ja': "tools/damo_asr/models/speech_UniASR_asr_2pass-ja-16k-common-vocab93-tensorflow1-offline",
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"en": "tools/damo_asr/models/speech_UniASR_asr_2pass-en-16k-common-vocab1080-tensorflow1-offline",
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}
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model = Model.from_pretrained(lang2model["zh"])
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition,
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model=model,
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vad_model='tools/damo_asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch',
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punc_model='tools/damo_asr/models/punc_ct-transformer_zh-cn-common-vocab272727-pytorch',
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)
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def process_audio_file(dir,filename,name,opt_name):
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try:
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text = inference_pipeline(audio_in="%s/%s" % (dir, name))["text"]
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with lock:
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with open(filename,"a",encoding="utf-8")as f:f.write("%s/%s|%s|ZH|%s\n" % (dir, name, opt_name, text))
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except:
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print(traceback.format_exc())
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def run__process(): # 主进程
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opt_dir="output/asr_opt"
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os.makedirs(opt_dir,exist_ok=True)
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filename = "%s/%s.list"%(opt_dir,opt_name)
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if os.path.exists(filename):
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os.remove(filename)
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with multiprocessing.Pool(processes=processes) as pool:
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pool.starmap(process_audio_file, [(dir,filename,name ,opt_name) for name in os.listdir(dir)])
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if __name__ == '__main__':
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run__process()
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