From 6baf10d5d15bed3948459b30567edd3c5898ff84 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 17 二月 2023 10:31:05 +0800
Subject: [PATCH] Merge branch 'main' into dev_zly

---
 funasr/utils/timestamp_tools.py |   82 -----------------------------------------
 1 files changed, 0 insertions(+), 82 deletions(-)

diff --git a/funasr/utils/timestamp_tools.py b/funasr/utils/timestamp_tools.py
index 33d1255..f966aee 100644
--- a/funasr/utils/timestamp_tools.py
+++ b/funasr/utils/timestamp_tools.py
@@ -4,88 +4,6 @@
 import numpy as np
 from typing import Any, List, Tuple, Union
 
-def cut_interval(alphas: torch.Tensor, start: int, end: int, tail: bool):
-    if not tail:
-        if end == start + 1:
-            cut = (end + start) / 2.0
-        else:
-            alpha = alphas[start+1: end].tolist()
-            reverse_steps = 1
-            for reverse_alpha in alpha[::-1]:
-                if reverse_alpha > 0.35:
-                    reverse_steps += 1
-                else:
-                    break
-            cut = end - reverse_steps
-    else:
-        if end != len(alphas) - 1:
-            cut = end + 1
-        else:
-            cut = start + 1
-    return float(cut)
-
-def time_stamp_lfr6(alphas: torch.Tensor, speech_lengths: torch.Tensor, raw_text: List[str], begin: int = 0, end: int = None):
-    time_stamp_list = []
-    alphas = alphas[0]
-    text = copy.deepcopy(raw_text)
-    if end is None:
-        time = speech_lengths * 60 / 1000
-        sacle_rate = (time / speech_lengths[0]).tolist()
-    else:
-        time = (end - begin) / 1000
-        sacle_rate = (time / speech_lengths[0]).tolist()
-
-    predictor = (alphas > 0.5).int()
-    fire_places = torch.nonzero(predictor == 1).squeeze(1).tolist()
-    
-    cuts = []
-    npeak = int(predictor.sum())
-    nchar = len(raw_text)
-    if npeak - 1 == nchar:
-        fire_places = torch.where((alphas > 0.5) == 1)[0].tolist()
-        for i in range(len(fire_places)):
-            if fire_places[i] < len(alphas) - 1:
-                if 0.05 < alphas[fire_places[i]+1] < 0.5:
-                    fire_places[i] += 1
-    elif npeak < nchar:
-        lost_num = nchar - npeak
-        lost_fire = speech_lengths[0].tolist() - fire_places[-1]
-        interval_distance = lost_fire // (lost_num + 1)
-        for i in range(1, lost_num + 1):
-            fire_places.append(fire_places[-1] + interval_distance)
-    elif npeak - 1 > nchar:
-        redundance_num = npeak - 1 - nchar
-        for i in range(redundance_num):
-            fire_places.pop() 
-
-    cuts.append(0)
-    start_sil = True
-    if start_sil:
-        text.insert(0, '<sil>')
-
-    for i in range(len(fire_places)-1):
-        cuts.append(cut_interval(alphas, fire_places[i], fire_places[i+1], tail=(i==len(fire_places)-2)))
-
-    for i in range(2, len(fire_places)-2):
-        if fire_places[i-2] == fire_places[i-1] - 1 and fire_places[i-1] != fire_places[i] - 1:
-            cuts[i-1] += 1
-
-    if cuts[-1] != len(alphas) - 1:
-        text.append('<sil>')
-        cuts.append(speech_lengths[0].tolist())
-    cuts.insert(-1, (cuts[-1] + cuts[-2]) * 0.5)
-    sec_fire_places = np.array(cuts) * sacle_rate
-    for i in range(1, len(sec_fire_places) - 1):
-        start, end = sec_fire_places[i], sec_fire_places[i+1]
-        if i == len(sec_fire_places) - 2:
-            end = time
-        time_stamp_list.append([int(round(start, 2) * 1000) + begin, int(round(end, 2) * 1000) + begin])
-        text = text[1:]
-    if npeak - 1 == nchar or npeak > nchar:
-        return time_stamp_list[:-1]
-    else:
-        return time_stamp_list
-
 def time_stamp_lfr6_pl(us_alphas, us_cif_peak, char_list, begin_time=0.0, end_time=None):
     START_END_THRESHOLD = 5
     TIME_RATE = 10.0 * 6 / 1000 / 3  #  3 times upsampled

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