| | |
| | | # step.3 compute punc model |
| | | if self.punc_model is not None: |
| | | if not len(result["text"]): |
| | | result['raw_text'] = '' |
| | | if return_raw_text: |
| | | result['raw_text'] = '' |
| | | else: |
| | | self.punc_kwargs.update(cfg) |
| | | punc_res = self.inference(result["text"], model=self.punc_model, kwargs=self.punc_kwargs, **cfg) |
| | |
| | | distribute_spk(sentence_list, sv_output) |
| | | result['sentence_info'] = sentence_list |
| | | elif kwargs.get("sentence_timestamp", False): |
| | | sentence_list = timestamp_sentence(punc_res[0]['punc_array'], |
| | | result['timestamp'], |
| | | raw_text, |
| | | return_raw_text=return_raw_text) |
| | | if not len(result['text']): |
| | | sentence_list = [] |
| | | else: |
| | | sentence_list = timestamp_sentence(punc_res[0]['punc_array'], |
| | | result['timestamp'], |
| | | raw_text, |
| | | return_raw_text=return_raw_text) |
| | | result['sentence_info'] = sentence_list |
| | | if "spk_embedding" in result: del result['spk_embedding'] |
| | | |