| | |
|---|
| | | tp_model, tp_train_args = ASRTask.build_model_from_file( |
|---|
| | | timestamp_infer_config, timestamp_model_file, device |
|---|
| | | ) |
|---|
| | | if 'cuda' in device: |
|---|
| | | tp_model = tp_model.cuda() |
|---|
| | | |
|---|
| | | frontend = None |
|---|
| | | if tp_train_args.frontend is not None: |
|---|
| | | frontend = WavFrontend(cmvn_file=timestamp_cmvn_file, **tp_train_args.frontend_conf) |
|---|
| | |
|---|
| | | device = "cuda" |
|---|
| | | else: |
|---|
| | | device = "cpu" |
|---|
| | | |
|---|
| | | # 1. Set random-seed |
|---|
| | | set_all_random_seed(seed) |
|---|
| | | |
|---|
| | |
|---|
| | | token = speechtext2timestamp.converter.ids2tokens(batch['text'][batch_id]) |
|---|
| | | ts_str, ts_list = time_stamp_lfr6_advance(us_alphas[batch_id], us_cif_peak[batch_id], token) |
|---|
| | | logging.warning(ts_str) |
|---|
| | | tp_result_list.append({'text':"".join([i for i in token if i != '<sil>']), 'timestamp': ts_list}) |
|---|
| | | item = {'key': key, 'value': ts_str, 'timestamp':ts_list} |
|---|
| | | # tp_result_list.append({'text':"".join([i for i in token if i != '<sil>']), 'timestamp': ts_list}) |
|---|
| | | tp_result_list.append(item) |
|---|
| | | return tp_result_list |
|---|
| | | |
|---|
| | | return _forward |
|---|
