| | |
| | | |
| | | |
| | | class CT_Transformer(): |
| | | """ |
| | | Author: Speech Lab of DAMO Academy, Alibaba Group |
| | | CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection |
| | | https://arxiv.org/pdf/2003.01309.pdf |
| | | """ |
| | | def __init__(self, model_dir: Union[str, Path] = None, |
| | | batch_size: int = 1, |
| | | device_id: Union[str, int] = "-1", |
| | |
| | | |
| | | |
| | | class CT_Transformer_VadRealtime(CT_Transformer): |
| | | """ |
| | | Author: Speech Lab of DAMO Academy, Alibaba Group |
| | | CT-Transformer: Controllable time-delay transformer for real-time punctuation prediction and disfluency detection |
| | | https://arxiv.org/pdf/2003.01309.pdf |
| | | """ |
| | | def __init__(self, model_dir: Union[str, Path] = None, |
| | | batch_size: int = 1, |
| | | device_id: Union[str, int] = "-1", |
| | |
| | | data = { |
| | | "input": mini_sentence_id[None,:], |
| | | "text_lengths": np.array([text_length], dtype='int32'), |
| | | "vad_mask": self.vad_mask(text_length, len(cache) - 1)[None, None, :, :].astype(np.float32), |
| | | "vad_mask": self.vad_mask(text_length, len(cache))[None, None, :, :].astype(np.float32), |
| | | "sub_masks": np.tril(np.ones((text_length, text_length), dtype=np.float32))[None, None, :, :].astype(np.float32) |
| | | } |
| | | try: |