| | |
|---|
| | | import torch |
|---|
| | | import copy |
|---|
| | | import codecs |
|---|
| | | import logging |
|---|
| | | import argparse |
|---|
| | | import numpy as np |
|---|
| | | from typing import Any, List, Tuple, Union |
|---|
| | | # import edit_distance |
|---|
| | | from itertools import zip_longest |
|---|
| | | |
|---|
| | | def time_stamp_lfr6_pl(us_alphas, us_cif_peak, char_list, begin_time=0.0, end_time=None): |
|---|
| | | |
|---|
| | | def cif_wo_hidden(alphas, threshold): |
|---|
| | | batch_size, len_time = alphas.size() |
|---|
| | | # loop varss |
|---|
| | | integrate = torch.zeros([batch_size], device=alphas.device) |
|---|
| | | # intermediate vars along time |
|---|
| | | list_fires = [] |
|---|
| | | for t in range(len_time): |
|---|
| | | alpha = alphas[:, t] |
|---|
| | | integrate += alpha |
|---|
| | | list_fires.append(integrate) |
|---|
| | | fire_place = integrate >= threshold |
|---|
| | | integrate = torch.where(fire_place, |
|---|
| | | integrate - torch.ones([batch_size], device=alphas.device)*threshold, |
|---|
| | | integrate) |
|---|
| | | fires = torch.stack(list_fires, 1) |
|---|
| | | return fires |
|---|
| | | |
|---|
| | | |
|---|
| | | def ts_prediction_lfr6_standard(us_alphas, |
|---|
| | | us_peaks, |
|---|
| | | char_list, |
|---|
| | | vad_offset=0.0, |
|---|
| | | force_time_shift=-1.5, |
|---|
| | | sil_in_str=True |
|---|
| | | ): |
|---|
| | | if not len(char_list): |
|---|
| | | return [] |
|---|
| | | return "", [] |
|---|
| | | START_END_THRESHOLD = 5 |
|---|
| | | MAX_TOKEN_DURATION = 12 |
|---|
| | | TIME_RATE = 10.0 * 6 / 1000 / 3 # 3 times upsampled |
|---|
| | | if len(us_alphas.shape) == 3: |
|---|
| | | alphas, cif_peak = us_alphas[0], us_cif_peak[0] # support inference batch_size=1 only |
|---|
| | | if len(us_alphas.shape) == 2: |
|---|
| | | alphas, peaks = us_alphas[0], us_peaks[0] # support inference batch_size=1 only |
|---|
| | | else: |
|---|
| | | alphas, cif_peak = us_alphas, us_cif_peak |
|---|
| | | num_frames = cif_peak.shape[0] |
|---|
| | | alphas, peaks = us_alphas, us_peaks |
|---|
| | | if char_list[-1] == '</s>': |
|---|
| | | char_list = char_list[:-1] |
|---|
| | | # char_list = [i for i in text] |
|---|
| | | 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 |
|---|
| | | 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(cif_peak>1.0-1e-4)[0].cpu().numpy() - 1.5 |
|---|
| | | num_peak = len(fire_place) |
|---|
| | | assert num_peak == len(char_list) + 1 # number of peaks is supposed to be number of tokens + 1 |
|---|
| | | 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: |
|---|
| | | char_list.insert(0, '<sil>') |
|---|
| | | # char_list.insert(0, '<sil>') |
|---|
| | | timestamp_list.append([0.0, fire_place[0]*TIME_RATE]) |
|---|
| | | new_char_list.append('<sil>') |
|---|
| | | # tokens timestamp |
|---|
| | | for i in range(len(fire_place)-1): |
|---|
| | | # the peak is always a little ahead of the start time |
|---|
| | | # timestamp_list.append([(fire_place[i]-1.2)*TIME_RATE, fire_place[i+1]*TIME_RATE]) |
|---|
| | | timestamp_list.append([(fire_place[i])*TIME_RATE, fire_place[i+1]*TIME_RATE]) |
|---|
| | | # cut the duration to token and sil of the 0-weight frames last long |
|---|
| | | new_char_list.append(char_list[i]) |
|---|
| | | if MAX_TOKEN_DURATION < 0 or fire_place[i+1] - fire_place[i] <= MAX_TOKEN_DURATION: |
|---|
| | | timestamp_list.append([fire_place[i]*TIME_RATE, fire_place[i+1]*TIME_RATE]) |
|---|
| | | else: |
|---|
| | | # cut the duration to token and sil of the 0-weight frames last long |
|---|
| | | _split = fire_place[i] + MAX_TOKEN_DURATION |
|---|
| | | timestamp_list.append([fire_place[i]*TIME_RATE, _split*TIME_RATE]) |
|---|
| | | timestamp_list.append([_split*TIME_RATE, fire_place[i+1]*TIME_RATE]) |
|---|
| | | new_char_list.append('<sil>') |
|---|
| | | # tail token and end silence |
|---|
| | | # new_char_list.append(char_list[-1]) |
|---|
| | | if num_frames - fire_place[-1] > START_END_THRESHOLD: |
|---|
| | | _end = (num_frames + fire_place[-1]) / 2 |
|---|
| | | _end = (num_frames + fire_place[-1]) * 0.5 |
|---|
| | | # _end = fire_place[-1] |
|---|
| | | timestamp_list[-1][1] = _end*TIME_RATE |
|---|
| | | timestamp_list.append([_end*TIME_RATE, num_frames*TIME_RATE]) |
|---|
| | | char_list.append("<sil>") |
|---|
| | | new_char_list.append("<sil>") |
|---|
| | | else: |
|---|
| | | timestamp_list[-1][1] = num_frames*TIME_RATE |
|---|
| | | if begin_time: # add offset time in model with vad |
|---|
| | | if vad_offset: # add offset time in model with vad |
|---|
| | | for i in range(len(timestamp_list)): |
|---|
| | | timestamp_list[i][0] = timestamp_list[i][0] + begin_time / 1000.0 |
|---|
| | | timestamp_list[i][1] = timestamp_list[i][1] + begin_time / 1000.0 |
|---|
| | | timestamp_list[i][0] = timestamp_list[i][0] + vad_offset / 1000.0 |
|---|
| | | timestamp_list[i][1] = timestamp_list[i][1] + vad_offset / 1000.0 |
|---|
| | | res_txt = "" |
|---|
| | | for char, timestamp in zip(char_list, timestamp_list): |
|---|
| | | res_txt += "{} {} {};".format(char, timestamp[0], timestamp[1]) |
|---|
| | | for char, timestamp in zip(new_char_list, timestamp_list): |
|---|
| | | #if char != '<sil>': |
|---|
| | | if not sil_in_str and char == '<sil>': continue |
|---|
| | | res_txt += "{} {} {};".format(char, str(timestamp[0]+0.0005)[:5], str(timestamp[1]+0.0005)[:5]) |
|---|
| | | res = [] |
|---|
| | | for char, timestamp in zip(char_list, timestamp_list): |
|---|
| | | for char, timestamp in zip(new_char_list, timestamp_list): |
|---|
| | | if char != '<sil>': |
|---|
| | | res.append([int(timestamp[0] * 1000), int(timestamp[1] * 1000)]) |
|---|
| | | return res |
|---|
| | | return res_txt, res |
|---|
| | | |
|---|
| | | def time_stamp_sentence(punc_id_list, time_stamp_postprocessed, text_postprocessed): |
|---|
| | | |
|---|
| | | def timestamp_sentence(punc_id_list, timestamp_postprocessed, text_postprocessed): |
|---|
| | | punc_list = ['，', '。', '？', '、'] |
|---|
| | | res = [] |
|---|
| | | if text_postprocessed is None: |
|---|
| | | return res |
|---|
| | | if time_stamp_postprocessed is None: |
|---|
| | | if timestamp_postprocessed is None: |
|---|
| | | return res |
|---|
| | | if len(time_stamp_postprocessed) == 0: |
|---|
| | | if len(timestamp_postprocessed) == 0: |
|---|
| | | return res |
|---|
| | | if len(text_postprocessed) == 0: |
|---|
| | | return res |
|---|
| | | |
|---|
| | | if punc_id_list is None or len(punc_id_list) == 0: |
|---|
| | | res.append({ |
|---|
| | | 'text': text_postprocessed.split(), |
|---|
| | | "start": time_stamp_postprocessed[0][0], |
|---|
| | | "end": time_stamp_postprocessed[-1][1] |
|---|
| | | "start": timestamp_postprocessed[0][0], |
|---|
| | | "end": timestamp_postprocessed[-1][1], |
|---|
| | | "timestamp": timestamp_postprocessed, |
|---|
| | | }) |
|---|
| | | return res |
|---|
| | | if len(punc_id_list) != len(time_stamp_postprocessed): |
|---|
| | | res.append({ |
|---|
| | | 'text': text_postprocessed.split(), |
|---|
| | | "start": time_stamp_postprocessed[0][0], |
|---|
| | | "end": time_stamp_postprocessed[-1][1] |
|---|
| | | }) |
|---|
| | | return res |
|---|
| | | |
|---|
| | | sentence_text = '' |
|---|
| | | sentence_start = time_stamp_postprocessed[0][0] |
|---|
| | | if len(punc_id_list) != len(timestamp_postprocessed): |
|---|
| | | logging.warning("length mismatch between punc and timestamp") |
|---|
| | | sentence_text = "" |
|---|
| | | sentence_text_seg = "" |
|---|
| | | ts_list = [] |
|---|
| | | sentence_start = timestamp_postprocessed[0][0] |
|---|
| | | sentence_end = timestamp_postprocessed[0][1] |
|---|
| | | texts = text_postprocessed.split() |
|---|
| | | for i in range(len(punc_id_list)): |
|---|
| | | sentence_text += texts[i] |
|---|
| | | if punc_id_list[i] == 2: |
|---|
| | | sentence_text += ',' |
|---|
| | | punc_stamp_text_list = list(zip_longest(punc_id_list, timestamp_postprocessed, texts, fillvalue=None)) |
|---|
| | | for punc_stamp_text in punc_stamp_text_list: |
|---|
| | | punc_id, timestamp, text = punc_stamp_text |
|---|
| | | # sentence_text += text if text is not None else '' |
|---|
| | | if text is not None: |
|---|
| | | if 'a' <= text[0] <= 'z' or 'A' <= text[0] <= 'Z': |
|---|
| | | sentence_text += ' ' + text |
|---|
| | | elif len(sentence_text) and ('a' <= sentence_text[-1] <= 'z' or 'A' <= sentence_text[-1] <= 'Z'): |
|---|
| | | sentence_text += ' ' + text |
|---|
| | | else: |
|---|
| | | sentence_text += text |
|---|
| | | sentence_text_seg += text + ' ' |
|---|
| | | ts_list.append(timestamp) |
|---|
| | | |
|---|
| | | punc_id = int(punc_id) if punc_id is not None else 1 |
|---|
| | | sentence_end = timestamp[1] if timestamp is not None else sentence_end |
|---|
| | | |
|---|
| | | if punc_id > 1: |
|---|
| | | sentence_text += punc_list[punc_id - 2] |
|---|
| | | res.append({ |
|---|
| | | 'text': sentence_text, |
|---|
| | | "start": sentence_start, |
|---|
| | | "end": time_stamp_postprocessed[i][1] |
|---|
| | | "end": sentence_end, |
|---|
| | | "timestamp": ts_list |
|---|
| | | }) |
|---|
| | | sentence_text = '' |
|---|
| | | sentence_start = time_stamp_postprocessed[i][1] |
|---|
| | | elif punc_id_list[i] == 3: |
|---|
| | | sentence_text += '.' |
|---|
| | | res.append({ |
|---|
| | | 'text': sentence_text, |
|---|
| | | "start": sentence_start, |
|---|
| | | "end": time_stamp_postprocessed[i][1] |
|---|
| | | }) |
|---|
| | | sentence_text = '' |
|---|
| | | sentence_start = time_stamp_postprocessed[i][1] |
|---|
| | | sentence_text_seg = '' |
|---|
| | | ts_list = [] |
|---|
| | | sentence_start = sentence_end |
|---|
| | | return res |
|---|
| | | |
|---|
| | | |
|---|
