| | |
|---|
| | | for i in range(n): |
|---|
| | | kwargs["is_final"] = _is_final and i == n -1 |
|---|
| | | audio_sample_i = audio_sample[i*chunk_stride_samples:(i+1)*chunk_stride_samples] |
|---|
| | | if kwargs["is_final"] and len(audio_sample_i) < 960: |
|---|
| | | continue |
|---|
| | | |
|---|
| | | # extract fbank feats |
|---|
| | | speech, speech_lengths = extract_fbank([audio_sample_i], data_type=kwargs.get("data_type", "sound"), |
|---|
| | |
|---|
| | | ibest_writer["text"][key[0]] = text_postprocessed |
|---|
| | | |
|---|
| | | return result, meta_data |
|---|
| | | |
|---|
| | | |
|---|
| | | |
|---|
| | | def export(self, **kwargs): |
|---|
| | | from .export_meta import export_rebuild_model |
|---|
| | | models = export_rebuild_model(model=self, **kwargs) |
|---|
| | | return models |
|---|
