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https://github.com/modelscope/FunASR
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@ -1349,10 +1349,7 @@ def inference_transducer(
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left_context=left_context,
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right_context=right_context,
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)
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speech2text = Speech2TextTransducer.from_pretrained(
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model_tag=model_tag,
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**speech2text_kwargs,
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)
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speech2text = Speech2TextTransducer(**speech2text_kwargs)
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def _forward(data_path_and_name_and_type,
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raw_inputs: Union[np.ndarray, torch.Tensor] = None,
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@ -92,10 +92,7 @@ def inference_sond(
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embedding_node="resnet1_dense"
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)
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logging.info("speech2xvector_kwargs: {}".format(speech2xvector_kwargs))
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speech2xvector = Speech2Xvector.from_pretrained(
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model_tag=model_tag,
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**speech2xvector_kwargs,
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)
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speech2xvector = Speech2Xvector(**speech2xvector_kwargs)
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speech2xvector.sv_model.eval()
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# 2b. Build speech2diar
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@ -109,10 +106,7 @@ def inference_sond(
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dur_threshold=dur_threshold,
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)
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logging.info("speech2diarization_kwargs: {}".format(speech2diar_kwargs))
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speech2diar = Speech2DiarizationSOND.from_pretrained(
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model_tag=model_tag,
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**speech2diar_kwargs,
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)
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speech2diar = Speech2DiarizationSOND(**speech2diar_kwargs)
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speech2diar.diar_model.eval()
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def output_results_str(results: dict, uttid: str):
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@ -257,10 +251,7 @@ def inference_eend(
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dtype=dtype,
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)
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logging.info("speech2diarization_kwargs: {}".format(speech2diar_kwargs))
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speech2diar = Speech2DiarizationEEND.from_pretrained(
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model_tag=model_tag,
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**speech2diar_kwargs,
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)
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speech2diar = Speech2DiarizationEEND(**speech2diar_kwargs)
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speech2diar.diar_model.eval()
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def output_results_str(results: dict, uttid: str):
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