| | |
|---|
| | | preds = self.decode(am_scores, valid_token_lens) |
|---|
| | | if us_cif_peak is None: |
|---|
| | | for pred in preds: |
|---|
| | | pred = sentence_postprocess(pred) |
|---|
| | | asr_res.append({'preds': pred}) |
|---|
| | | else: |
|---|
| | | for pred, us_cif_peak_ in zip(preds, us_cif_peak): |
|---|
| | | text, tokens = pred |
|---|
| | | timestamp, timestamp_total = time_stamp_lfr6_onnx(us_cif_peak_, copy.copy(tokens)) |
|---|
| | | raw_tokens = pred |
|---|
| | | timestamp, timestamp_raw = time_stamp_lfr6_onnx(us_cif_peak_, copy.copy(raw_tokens)) |
|---|
| | | text_proc, timestamp_proc, _ = sentence_postprocess(raw_tokens, timestamp_raw) |
|---|
| | | # logging.warning(timestamp) |
|---|
| | | if len(self.plot_timestamp_to): |
|---|
| | | self.plot_wave_timestamp(waveform_list[0], timestamp_total, self.plot_timestamp_to) |
|---|
| | | asr_res.append({'preds': text, 'timestamp': timestamp}) |
|---|
| | | self.plot_wave_timestamp(waveform_list[0], timestamp, self.plot_timestamp_to) |
|---|
| | | asr_res.append({'preds': text_proc, 'timestamp': timestamp_proc, "raw_tokens": raw_tokens}) |
|---|
| | | return asr_res |
|---|
| | | |
|---|
| | | def plot_wave_timestamp(self, wav, text_timestamp, dest): |
|---|
| | |
|---|
| | | # Change integer-ids to tokens |
|---|
| | | token = self.converter.ids2tokens(token_int) |
|---|
| | | token = token[:valid_token_num-self.pred_bias] |
|---|
| | | texts = sentence_postprocess(token) |
|---|
| | | return texts |
|---|
| | | # texts = sentence_postprocess(token) |
|---|
| | | return token |
|---|
| | | |
|---|
