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| | | from funasr.utils.speaker_utils import (check_audio_list, |
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| | | sv_preprocess, |
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| | | sv_chunk, |
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| | | CAMPPlus, |
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| | | extract_feature, |
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| | | postprocess, |
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| | | distribute_spk, ERes2Net) |
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| | | distribute_spk) |
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| | | import funasr.modules.cnn as sv_module |
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| | | from funasr.build_utils.build_model_from_file import build_model_from_file |
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| | | from funasr.utils.cluster_backend import ClusterBackend |
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| | | from funasr.utils.modelscope_utils import get_cache_dir |
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| | |
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| | | format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s", |
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| | | ) |
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| | | |
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| | | sv_model_file = asr_model_file.replace("model.pb", "campplus_cn_common.bin") |
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| | | if not os.path.exists(sv_model_file): |
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| | | sv_model_file = asr_model_file.replace("model.pb", "pretrained_eres2net_aug.ckpt") |
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| | | if not os.path.exists(sv_model_file): |
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| | | raise FileNotFoundError("sv_model_file not found: {}".format(sv_model_file)) |
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| | | sv_model_config_path = asr_model_file.replace("model.pb", "sv_model_config.yaml") |
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| | | if not os.path.exists(sv_model_config_path): |
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| | | sv_model_config = {'sv_model_class': 'CAMPPlus','sv_model_file': 'campplus_cn_common.bin', 'models_config': {}} |
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| | | else: |
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| | | with open(sv_model_config_path, 'r') as f: |
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| | | sv_model_config = yaml.load(f, Loader=yaml.FullLoader) |
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| | | if sv_model_config['models_config'] is None: |
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| | | sv_model_config['models_config'] = {} |
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| | | sv_model_file = asr_model_file.replace("model.pb", sv_model_config['sv_model_file']) |
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| | | |
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| | | if param_dict is not None: |
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| | | hotword_list_or_file = param_dict.get('hotword') |
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| | |
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| | | ################################## |
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| | | # load sv model |
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| | | sv_model_dict = torch.load(sv_model_file) |
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| | | print(f'load sv model params: {sv_model_file}') |
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| | | if os.path.basename(sv_model_file) == "campplus_cn_common.bin": |
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| | | sv_model = CAMPPlus() |
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| | | else: |
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| | | sv_model = ERes2Net() |
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| | | sv_model = getattr(sv_module, sv_model_config['sv_model_class'])(**sv_model_config['models_config']) |
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| | | if ngpu > 0: |
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| | | sv_model.cuda() |
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| | | sv_model.load_state_dict(sv_model_dict) |
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| | | print(f'load sv model params: {sv_model_file}') |
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| | | sv_model.eval() |
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| | | cb_model = ClusterBackend() |
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| | | vad_segments = [] |
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