| | |
|---|
| | | fbanks, fbanks_len = self.frontend.forward_fbank(speech, speech_lengths) |
|---|
| | | feats, feats_len = self.frontend.forward_lfr_cmvn(fbanks, fbanks_len) |
|---|
| | | fbanks = to_device(fbanks, device=self.device) |
|---|
| | | # feats = to_device(feats, device=self.device) |
|---|
| | | feats = to_device(feats, device=self.device) |
|---|
| | | feats_len = feats_len.int() |
|---|
| | | else: |
|---|
| | | raise Exception("Need to extract feats first, please configure frontend configuration") |
|---|
| | |
|---|
| | | "in_cache": in_cache |
|---|
| | | } |
|---|
| | | # a. To device |
|---|
| | | batch = to_device(batch, device=self.device) |
|---|
| | | #batch = to_device(batch, device=self.device) |
|---|
| | | segments_part, in_cache = self.vad_model(**batch) |
|---|
| | | if segments_part: |
|---|
| | | for batch_num in range(0, self.batch_size): |
|---|
| | |
|---|
| | | assert check_argument_types() |
|---|
| | | if batch_size > 1: |
|---|
| | | raise NotImplementedError("batch decoding is not implemented") |
|---|
| | | if ngpu > 1: |
|---|
| | | raise NotImplementedError("only single GPU decoding is supported") |
|---|
| | | |
|---|
| | | |
|---|
| | | logging.basicConfig( |
|---|
| | | level=log_level, |
|---|
| | |
|---|
| | | device = "cuda" |
|---|
| | | else: |
|---|
| | | device = "cpu" |
|---|
| | | |
|---|
| | | batch_size = 1 |
|---|
| | | # 1. Set random-seed |
|---|
| | | set_all_random_seed(seed) |
|---|
| | | |
|---|
| | |
|---|
| | | item = {'key': keys[i], 'value': results[i]} |
|---|
| | | vad_results.append(item) |
|---|
| | | if writer is not None: |
|---|
| | | results[i] = json.loads(results[i]) |
|---|
| | | ibest_writer["text"][keys[i]] = "{}".format(results[i]) |
|---|
| | | |
|---|
| | | return vad_results |
|---|
| | |
|---|
| | | **kwargs, |
|---|
| | | ): |
|---|
| | | assert check_argument_types() |
|---|
| | | if batch_size > 1: |
|---|
| | | raise NotImplementedError("batch decoding is not implemented") |
|---|
| | | if ngpu > 1: |
|---|
| | | raise NotImplementedError("only single GPU decoding is supported") |
|---|
| | | |
|---|
| | | |
|---|
| | | logging.basicConfig( |
|---|
| | | level=log_level, |
|---|
| | |
|---|
| | | device = "cuda" |
|---|
| | | else: |
|---|
| | | device = "cpu" |
|---|
| | | batch_size = 1 |
|---|
| | | |
|---|
| | | # 1. Set random-seed |
|---|
| | | set_all_random_seed(seed) |
|---|
| | |
|---|
| | | item = {'key': keys[i], 'value': results[i]} |
|---|
| | | vad_results.append(item) |
|---|
| | | if writer is not None: |
|---|
| | | results[i] = json.loads(results[i]) |
|---|
| | | ibest_writer["text"][keys[i]] = "{}".format(results[i]) |
|---|
| | | |
|---|
| | | return vad_results |
|---|
