From e33bb15d269bb3e2e41f7a3540d9b92703bb5c50 Mon Sep 17 00:00:00 2001
From: aky15 <ankeyu.aky@11.17.44.249>
Date: 星期三, 15 三月 2023 10:51:52 +0800
Subject: [PATCH] Merge branch 'main' into dev_aky

---
 funasr/utils/timestamp_tools.py |   56 +++++++++++++++++++++++++++++++++++---------------------
 1 files changed, 35 insertions(+), 21 deletions(-)

diff --git a/funasr/utils/timestamp_tools.py b/funasr/utils/timestamp_tools.py
index 4a367f8..f5a238e 100644
--- a/funasr/utils/timestamp_tools.py
+++ b/funasr/utils/timestamp_tools.py
@@ -5,55 +5,69 @@
 from typing import Any, List, Tuple, Union
 
 
-def time_stamp_lfr6_pl(us_alphas, us_cif_peak, char_list, begin_time=0.0, end_time=None):
+def ts_prediction_lfr6_standard(us_alphas, 
+                       us_peaks, 
+                       char_list, 
+                       vad_offset=0.0, 
+                       force_time_shift=-1.5
+                       ):
     if not len(char_list):
         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:
+        _, 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]
+        _, peaks = us_alphas, us_peaks
+    num_frames = peaks.shape[0]
     if char_list[-1] == '</s>':
         char_list = char_list[:-1]
-    # char_list = [i for i in text]
     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
+    fire_place = torch.where(peaks>1.0-1e-4)[0].cpu().numpy() + force_time_shift  # total offset
     num_peak = len(fire_place)
     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):
+        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):

--
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