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@@ -64,23 +64,23 @@ class Paraformer():
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am_scores, valid_token_lens = outputs[0], outputs[1]
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if len(outputs) == 4:
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# for BiCifParaformer Inference
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- us_alphas, us_cif_peak = outputs[2], outputs[3]
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+ us_alphas, us_peaks = outputs[2], outputs[3]
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else:
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- us_alphas, us_cif_peak = None, None
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+ us_alphas, us_peaks = None, None
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except ONNXRuntimeError:
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#logging.warning(traceback.format_exc())
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logging.warning("input wav is silence or noise")
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preds = ['']
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else:
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preds = self.decode(am_scores, valid_token_lens)
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- if us_cif_peak is None:
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+ if us_peaks is None:
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for pred in preds:
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pred = sentence_postprocess(pred)
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asr_res.append({'preds': pred})
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else:
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- for pred, us_cif_peak_ in zip(preds, us_cif_peak):
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+ for pred, us_peaks_ in zip(preds, us_peaks):
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raw_tokens = pred
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- timestamp, timestamp_raw = time_stamp_lfr6_onnx(us_cif_peak_, copy.copy(raw_tokens))
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+ timestamp, timestamp_raw = time_stamp_lfr6_onnx(us_peaks_, copy.copy(raw_tokens))
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text_proc, timestamp_proc, _ = sentence_postprocess(raw_tokens, timestamp_raw)
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# logging.warning(timestamp)
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if len(self.plot_timestamp_to):
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