<<<<<<< HEAD
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import os
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import shutil
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import argparse
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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def modelscope_infer(args):
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os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpuid)
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition,
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model=args.model,
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output_dir=args.output_dir,
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batch_size=args.batch_size,
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param_dict={"decoding_model": args.decoding_mode, "hotword": args.hotword_txt}
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)
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inference_pipeline(audio_in=args.audio_in)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('--model', type=str, default="damo/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch")
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parser.add_argument('--audio_in', type=str, default="./data/test/wav.scp")
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parser.add_argument('--output_dir', type=str, default="./results/")
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parser.add_argument('--decoding_mode', type=str, default="normal")
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parser.add_argument('--hotword_txt', type=str, default=None)
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parser.add_argument('--batch_size', type=int, default=64)
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parser.add_argument('--gpuid', type=str, default="0")
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args = parser.parse_args()
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modelscope_infer(args)
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=======
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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if __name__ == "__main__":
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audio_in = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_tr.wav"
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output_dir = "./results"
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inference_pipeline = pipeline(
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task=Tasks.auto_speech_recognition,
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model="damo/speech_UniASR_asr_2pass-tr-16k-common-vocab1582-pytorch",
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output_dir=output_dir,
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)
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rec_result = inference_pipeline(audio_in=audio_in, param_dict={"decoding_model":"offline"})
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print(rec_result)
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>>>>>>> main
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