| | |
|---|
| | | quantize_dtype: str = "qint8", |
|---|
| | | nbest: int = 1, |
|---|
| | | streaming: bool = False, |
|---|
| | | simu_streaming: bool = False, |
|---|
| | | fake_streaming: bool = False, |
|---|
| | | full_utt: bool = False, |
|---|
| | | chunk_size: int = 16, |
|---|
| | | left_context: int = 32, |
|---|
| | |
|---|
| | | |
|---|
| | | self.beam_search = beam_search |
|---|
| | | self.streaming = streaming |
|---|
| | | self.simu_streaming = simu_streaming |
|---|
| | | self.fake_streaming = fake_streaming |
|---|
| | | self.full_utt = full_utt |
|---|
| | | self.chunk_size = max(chunk_size, 0) |
|---|
| | | self.left_context = left_context |
|---|
| | |
|---|
| | | self.streaming = False |
|---|
| | | self.asr_model.encoder.dynamic_chunk_training = False |
|---|
| | | |
|---|
| | | if not simu_streaming or chunk_size == 0: |
|---|
| | | self.simu_streaming = False |
|---|
| | | if not fake_streaming or chunk_size == 0: |
|---|
| | | self.fake_streaming = False |
|---|
| | | self.asr_model.encoder.dynamic_chunk_training = False |
|---|
| | | |
|---|
| | | self.frontend = frontend |
|---|
| | |
|---|
| | | return nbest_hyps |
|---|
| | | |
|---|
| | | @torch.no_grad() |
|---|
| | | def simu_streaming_decode(self, speech: Union[torch.Tensor, np.ndarray]) -> List[HypothesisTransducer]: |
|---|
| | | def fake_streaming_decode(self, speech: Union[torch.Tensor, np.ndarray]) -> List[HypothesisTransducer]: |
|---|
| | | """Speech2Text call. |
|---|
| | | Args: |
|---|
| | | speech: Speech data. (S) |
|---|
