| | |
|---|
| | | feats = cache_en["feats"] |
|---|
| | | feats_len = torch.tensor([feats.shape[1]]) |
|---|
| | | self.asr_model.frontend = None |
|---|
| | | self.frontend.cache_reset() |
|---|
| | | results = self.infer(feats, feats_len, cache) |
|---|
| | | return results |
|---|
| | | else: |
|---|
| | | if self.frontend is not None: |
|---|
| | | if cache_en["start_idx"] == 0: |
|---|
| | | self.frontend.cache_reset() |
|---|
| | | feats, feats_len = self.frontend.forward(speech, speech_lengths, cache_en["is_final"]) |
|---|
| | | feats = to_device(feats, device=self.device) |
|---|
| | | feats_len = feats_len.int() |
|---|
| | |
|---|
| | | d = ModelDownloader() |
|---|
| | | kwargs.update(**d.download_and_unpack(model_tag)) |
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| | | |
|---|
| | | return Speech2Text(**kwargs) |
|---|
| | | return Speech2TextTransducer(**kwargs) |
|---|
| | | |
|---|
| | | |
|---|
| | | class Speech2TextSAASR: |
|---|
