| | |
|---|
| | | alphas, peaks = us_alphas, us_peaks |
|---|
| | | if char_list[-1] == '</s>': |
|---|
| | | char_list = char_list[:-1] |
|---|
| | | fire_place = torch.where(peaks>1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | fire_place = torch.where(peaks>=1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | if len(fire_place) != len(char_list) + 1: |
|---|
| | | alphas /= (alphas.sum() / (len(char_list) + 1)) |
|---|
| | | alphas = alphas.unsqueeze(0) |
|---|
| | | peaks = cif_wo_hidden(alphas, threshold=1.0-1e-4)[0] |
|---|
| | | fire_place = torch.where(peaks>1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | fire_place = torch.where(peaks>=1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | num_frames = peaks.shape[0] |
|---|
| | | timestamp_list = [] |
|---|
| | | new_char_list = [] |
|---|
| | | # for bicif model trained with large data, cif2 actually fires when a character starts |
|---|
| | | # so treat the frames between two peaks as the duration of the former token |
|---|
| | | fire_place = torch.where(peaks>1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | # fire_place = torch.where(peaks>=1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset |
|---|
| | | # assert num_peak == len(char_list) + 1 # number of peaks is supposed to be number of tokens + 1 |
|---|
| | | # begin silence |
|---|
| | | if fire_place[0] > START_END_THRESHOLD: |
|---|
