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https://github.com/modelscope/FunASR
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update preset_spk_num
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@ -11,18 +11,22 @@ model = AutoModel(model="iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-com
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vad_model_revision="v2.0.4",
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punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch",
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punc_model_revision="v2.0.4",
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# spk_model="damo/speech_campplus_sv_zh-cn_16k-common",
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# spk_model_revision="v2.0.2",
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spk_model="damo/speech_campplus_sv_zh-cn_16k-common",
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spk_model_revision="v2.0.2",
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)
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# example1
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res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
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hotword='达摩院 魔搭',
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# preset_spk_num=2,
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# sentence_timestamp=True, # return sentence level information when spk_model is not given
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)
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print(res)
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'''
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# tensor or numpy as input
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# example2
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import torchaudio
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import os
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@ -38,4 +42,4 @@ import soundfile
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wav_file = os.path.join(model.model_path, "example/asr_example.wav")
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speech, sample_rate = soundfile.read(wav_file)
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res = model.generate(input=[speech], batch_size_s=300, is_final=True)
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'''
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@ -121,9 +121,6 @@ class AutoModel:
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if spk_mode not in ["default", "vad_segment", "punc_segment"]:
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logging.error("spk_mode should be one of default, vad_segment and punc_segment.")
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self.spk_mode = spk_mode
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self.preset_spk_num = kwargs.get("preset_spk_num", None)
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if self.preset_spk_num:
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logging.warning("Using preset speaker number: {}".format(self.preset_spk_num))
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self.kwargs = kwargs
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self.model = model
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@ -391,7 +388,7 @@ class AutoModel:
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if self.spk_model is not None:
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all_segments = sorted(all_segments, key=lambda x: x[0])
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spk_embedding = result['spk_embedding']
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labels = self.cb_model(spk_embedding.cpu(), oracle_num=self.preset_spk_num)
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labels = self.cb_model(spk_embedding.cpu(), oracle_num=kwargs['preset_spk_num'])
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del result['spk_embedding']
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sv_output = postprocess(all_segments, None, labels, spk_embedding.cpu())
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if self.spk_mode == 'vad_segment': # recover sentence_list
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