如何将字幕文件转换为每个字幕只有一句话？

Question

我正在尝试编程一个方法来转换字幕文件，以便总是有一个句子每个字幕。

我的想法如下：

每个副标题的

1. ：

1.1 ->我得到字幕时长

1.2 ->计算characters_per_second

1.3 ->使用它(在dict_times_word_subtitle内部)存储说出单词i所需的时间

1. I从整个文本中提取句子

每句话的

1. ：

3.1我存储(在dict_sentences_subtitle中)用特定单词说出句子所需的时间(我可以从中获得说出它们的持续时间)

1. 我创建了一个新的srt文件(字幕文件)，它与原始srt文件同时开始，然后可以从说出句子的持续时间中获取字幕计时。

到目前为止，我已经编写了以下代码：

#---------------------------------------------------------
import pysrt
import re
from datetime import datetime, date, time, timedelta
#---------------------------------------------------------

def convert_subtitle_one_sentence(file_name):
    
    sub = pysrt.open(file_name)   

    ### ----------------------------------------------------------------------
    ### Store Each Word and the Average Time it Takes to Say it in a dictionary
    ### ----------------------------------------------------------------------

    dict_times_word_subtitle = {}
    running_variable = 0
    for i in range(len(sub)):

        subtitle_text = sub[i].text
        subtitle_duration = (datetime.combine(date.min, sub[i].duration.to_time()) - datetime.min).total_seconds()

        # Compute characters per second
        characters_per_second = len(subtitle_text)/subtitle_duration

        # Store Each Word and the Average Time (seconds) it Takes to Say in a Dictionary 
        
        for j,word in enumerate(subtitle_text.split()):
            if j == len(subtitle_text.split())-1:
                time = len(word)/characters_per_second
            else:
                time = len(word+" ")/characters_per_second

            dict_times_word_subtitle[str(running_variable)] = [word, time]
            running_variable += 1

            
    ### ----------------------------------------------------------------------
    ### Store Each Sentence and the Average Time to Say it in a Dictionary
    ### ----------------------------------------------------------------------  

    total_number_of_words = len(dict_times_word_subtitle.keys())

    # Get the entire text
    entire_text = ""
    for i in range(total_number_of_words):
        entire_text += dict_times_word_subtitle[str(i)][0] +" "


    # Initialize the dictionary 
    dict_times_sentences_subtitle = {}

    # Loop through all found sentences 
    last_number_of_words = 0
    for i,sentence in enumerate(re.findall(r'([A-Z][^\.!?]*[\.!?])', entire_text)):

        number_of_words = len(sentence.split())

        # Compute the time it takes to speak the sentence
        time_sentence = 0
        for j in range(last_number_of_words, last_number_of_words + number_of_words):
            time_sentence += dict_times_word_subtitle[str(j)][1] 

        # Store the sentence together with the time it takes to say the sentence
        dict_times_sentences_subtitle[str(i)] = [sentence, round(time_sentence,3)]

        ## Update last number_of_words
        last_number_of_words += number_of_words

    # Check if there is a non-sentence remaining at the end
    if j < total_number_of_words:
        remaining_string = ""
        remaining_string_time = 0
        for k in range(j+1, total_number_of_words):
            remaining_string += dict_times_word_subtitle[str(k)][0] + " "
            remaining_string_time += dict_times_word_subtitle[str(k)][1]

        dict_times_sentences_subtitle[str(i+1)] = [remaining_string, remaining_string_time]

    ### ----------------------------------------------------------------------
    ### Create a new Subtitle file with only 1 sentence at a time
    ### ----------------------------------------------------------------------  

    # Initalize new srt file
    new_srt = pysrt.SubRipFile()

    # Loop through all sentence
    # get initial start time (seconds)
    # https://stackoverflow.com/questions/44823073/convert-datetime-time-to-seconds
    start_time = (datetime.combine(date.min, sub[0].start.to_time()) - datetime.min).total_seconds()

    for i in range(len(dict_times_sentences_subtitle.keys())):


        sentence = dict_times_sentences_subtitle[str(i)][0]
        print(sentence)
        time_sentence = dict_times_sentences_subtitle[str(i)][1]
        print(time_sentence)
        item = pysrt.SubRipItem(
                        index=i,
                        start=pysrt.SubRipTime(seconds=start_time),
                        end=pysrt.SubRipTime(seconds=start_time+time_sentence),
                        text=sentence)

        new_srt.append(item)

        ## Update Start Time
        start_time += time_sentence

    new_srt.save(file_name)

问题是：

没有错误消息，但当我将其应用于实际的字幕文件，然后观看视频时，字幕开始正确，但随着视频的进行(错误进度)，字幕与实际所说的内容越来越不一致。

演讲者已经讲完了，但字幕还在不断出现。

​

​

要测试的简单示例

srt = """
1
00:00:13,100 --> 00:00:14,750
Dr. Martin Luther King, Jr.,

2
00:00:14,750 --> 00:00:18,636
in a 1968 speech where he reflects
upon the Civil Rights Movement,

3
00:00:18,636 --> 00:00:21,330
states, "In the end,

4
00:00:21,330 --> 00:00:24,413
we will remember not the words of our enemies

5
00:00:24,413 --> 00:00:27,280
but the silence of our friends."

6
00:00:27,280 --> 00:00:29,800
As a teacher, I've internalized this message.

"""

with open('test.srt', "w") as file:
    file.write(srt)
    
    
convert_subtitle_one_sentence("test.srt")

输出如下所示(是的，在句子识别par (即Dr. )上仍有一些工作要做)：

0 00:00:13,100 --> 00:00:13,336 Dr. 1 00:00:13,336 --> 00:00:14,750 Martin Luther King，Jr.2 00:00:14,750 --> 00:00:23,514民权运动，声明：“最终，我们将记住的不是敌人的言语，而是朋友的沉默。3 00:00:23,514 --> 00:00:26,175作为一名教师，我内化了这条信息。4 00:00:26,175 --> 00:00:29,859我们的朋友。”作为一名教师，我已经内化了这条信息。

正如您所看到的，原始的最后一个时间戳是00:00:29,800，而在输出文件中是00:00:29,859。这在一开始可能看起来不是很多，但随着视频的变长，差异也会增加。

完整的样本视频可以在这里下载：https://ufile.io/19nuvqb3

完整字幕文件：https://ufile.io/qracb7ai

注意:字幕文件将被覆盖，因此您可能需要存储另一个名称的副本以便能够进行比较。

方法如何修复它：

原始字幕的单词开始或结束的确切时间是已知的。这可以用于交叉检查和相应地调整定时。

编辑

这是一个创建字典的代码，该字典存储字符、character_duration (字幕上的平均)和开始或结束原始时间戳(如果该字符存在的话)。

sub = pysrt.open('video.srt')

running_variable = 0
dict_subtitle = {}

for i in range(len(sub)):

    # Extract Start Time Stamb
    timestamb_start = sub[i].start

    # Extract Text
    text =sub[i].text

    # Extract End Time Stamb
    timestamb_end = sub[i].end

    # Extract Characters per Second 
    characters_per_second = sub[i].characters_per_second
    
    # Fill Dictionary 
    for j,character in enumerate(" ".join(text.split())):
        character_duration = len(character)*characters_per_second
        dict_subtitle[str(running_variable)] = [character,character_duration,False, False]
        if j == 0: dict_subtitle[str(running_variable)] = [character, character_duration, timestamb_start, False]
        if j == len(text)-1 : dict_subtitle[str(running_variable)] = [character, character_duration, False, timestamb_end]
        running_variable += 1

更多视频可供尝试

您可以在此处下载更多视频及其相应的字幕文件：https://filebin.net/kwygjffdlfi62pjs

编辑3

4
00:00:18,856 --> 00:00:25,904
Je rappelle la définition de ce qu'est un produit scalaire, <i>dot product</i> dans <i>Ⅎ</i>.

5
00:00:24,855 --> 00:00:30,431
Donc je prends deux vecteurs dans <i>Ⅎ</i> et je définis cette opération-là, linéaire, <i>u 

Answer 1

根据请求，我已经重新编码以依赖于pysrt包和少量的re。

我们的想法是构建一个基于start_times的字典。

如果存在开始时间，则会将该时间的数据添加到条目中，但同时会更新end_time，因此结束时间会随文本一起前进。

如果不存在开始时间，它只是一个新的字典条目。

只有当我们知道一个句子已经完成时，开始时间才会提前。

因此，本质上，我们开始构建一个具有固定开始时间的句子。通过添加更多文本并更新结束时间，继续构建句子，直到句子结束。在这里，我们使用当前记录来提前开始时间，我们知道这是一个新句子。

包含多个句子的副标题条目被分解，在分解之前，使用整个副标题条目的pysrt character_per_second条目计算开始和结束时间。

最后，从字典中的条目将新的字幕文件写入磁盘。

显然，只有一个文件可以操作，我很可能会错过一些字幕布局驼峰，但至少它给了你一个工作的起点。

代码从头到尾都是注释的，所以大多数事情都应该是清楚的，比如如何和为什么。

编辑:我改进了对现有字典开始时间的检查，并更改了用于确定句子是否结束的方法，即在拆分后将句号放回文本中。

你提到的第二个视频确实有一些小标题，首先，请注意根本没有毫秒值。

以下代码在第二个视频上做得很好，在第一个视频上做得很好。

编辑2:添加了连续的句号和html <>标记删除

编辑3:原来pysrt从每秒字符数的计算中去掉了html标记。我现在也这样做了，这意味着可以在副标题中保留<html>格式。

编辑4:这个版本处理了数学和化学公式中的句号，加上ip数字等。基本上句号不意味着句号的地方。它还允许句子以?结尾。还有！

import pysrt
import re

abbreviations = ['Dr.','Mr.','Mrs.','Ms.','etc.','Jr.','e.g.'] # You get the idea!
abbrev_replace = ['Dr','Mr','Mrs','Ms','etc','Jr','eg']
subs = pysrt.open('new.srt')
subs_dict = {}          # Dictionary to accumulate new sub-titles (start_time:[end_time,sentence])
start_sentence = True   # Toggle this at the start and end of sentences

# regex to remove html tags from the character count
tags = re.compile(r'<.*?>')

# regex to split on ".", "?" or "!" ONLY if it is preceded by something else
# which is not a digit and is not a space. (Not perfect but close enough)
# Note: ? and ! can be an issue in some languages (e.g. french) where both ? and !
# are traditionally preceded by a space ! rather than!
end_of_sentence = re.compile(r'([^\s\0-9][\.\?\!])')

# End of sentence characters
eos_chars = set([".","?","!"])

for sub in subs:
    if start_sentence:
        start_time = sub.start
        start_sentence = False
    text = sub.text

    #Remove multiple full-stops e.g. "and ....."
    text = re.sub('\.+', '.', text)

    # Optional
    for idx, abr in enumerate(abbreviations):
        if abr in text:
            text = text.replace(abr,abbrev_replace[idx])
    # A test could also be made for initials in names i.e. John E. Rotten - showing my age there ;)

    multi = re.split(end_of_sentence,text.strip())
    cps = sub.characters_per_second

    # Test for a sub-title with multiple sentences
    if len(multi) > 1:
        # regex end_of_sentence breaks sentence start and sentence end into 2 parts
        # we need to put them back together again.
        # hence the odd range because the joined end part is then deleted
        for cnt in range(divmod(len(multi),2)[0]): # e.g. len=3 give 0 | 5 gives 0,1  | 7 gives 0,1,2
            multi[cnt] = multi[cnt] + multi[cnt+1]
            del multi[cnt+1]

        for part in multi:
            if len(part): # Avoid blank parts
                pass
            else:
                continue
            # Convert start time to seconds
            h,m,s,milli = re.split(':|,',str(start_time))
            s_time = (3600*int(h))+(60*int(m))+int(s)+(int(milli)/1000)

            # test for existing data
            try:
                existing_data = subs_dict[str(start_time)]
                end_time = str(existing_data[0])
                h,m,s,milli = re.split(':|,',str(existing_data[0]))
                e_time = (3600*int(h))+(60*int(m))+int(s)+(int(milli)/1000)
            except:
                existing_data = []
                e_time = s_time

            # End time is the start time or existing end time + the time taken to say the current words
            # based on the calculated number of characters per second
            # use regex "tags" to remove any html tags from the character count.

            e_time = e_time + len(tags.sub('',part)) / cps

            # Convert start to a timestamp
            s,milli = divmod(s_time,1)
            m,s = divmod(int(s),60)
            h,m = divmod(m,60)
            start_time = "{:02d}:{:02d}:{:02d},{:03d}".format(h,m,s,round(milli*1000))

            # Convert end to a timestamp
            s,milli = divmod(e_time,1)
            m,s = divmod(int(s),60)
            h,m = divmod(m,60)
            end_time = "{:02d}:{:02d}:{:02d},{:03d}".format(h,m,s,round(milli*1000))

            # if text already exists add the current text to the existing text
            # if not use the current text to write/rewrite the dictionary entry
            if existing_data:
                new_text = existing_data[1] + " " + part
            else:
                new_text = part
            subs_dict[str(start_time)] = [end_time,new_text]

            # if sentence ends re-set the current start time to the end time just calculated
            if any(x in eos_chars for x in part):
                start_sentence = True
                start_time = end_time
                print ("Split",start_time,"-->",end_time,)
                print (new_text)
                print('\n')
            else:
                start_sentence = False

    else:   # This is Not a multi-part sub-title

        end_time = str(sub.end)

        # Check for an existing dictionary entry for this start time
        try:
            existing_data = subs_dict[str(start_time)]
        except:
            existing_data = []

        # if it already exists add the current text to the existing text
        # if not use the current text
        if existing_data:
            new_text = existing_data[1] + " " + text
        else:
            new_text = text
        # Create or Update the dictionary entry for this start time
        # with the updated text and the current end time
        subs_dict[str(start_time)] = [end_time,new_text]

        if any(x in eos_chars for x in text):
            start_sentence = True
            print ("Single",start_time,"-->",end_time,)
            print (new_text)
            print('\n')
        else:
            start_sentence = False

# Generate the new sub-title file from the dictionary
idx=0
outfile = open('video_new.srt','w')
for key, text in subs_dict.items():
    idx+=1
    outfile.write(str(idx)+"\n")
    outfile.write(key+" --> "+text[0]+"\n")
    outfile.write(text[1]+"\n\n")
outfile.close()

传递上述video.srt文件代码后的输出如下所示：

1
00:00:13,100 --> 00:00:27,280
Dr Martin Luther King, Jr, in a 1968 speech where he reflects
upon the Civil Rights Movement, states, "In the end, we will remember not the words of our enemies but the silence of our friends."

2
00:00:27,280 --> 00:00:29,800
As a teacher, I've internalized this message.

3
00:00:29,800 --> 00:00:39,701
Every day, all around us, we see the consequences of silence manifest themselves in the form of discrimination, violence, genocide and war.

4
00:00:39,701 --> 00:00:46,178
In the classroom, I challenge my students to explore the silences in their own lives through poetry.

5
00:00:46,178 --> 00:00:54,740
We work together to fill those spaces, to recognize them, to name them, to understand that they don't
have to be sources of shame.

6
00:00:54,740 --> 00:01:14,408
In an effort to create a culture within my classroom where students feel safe sharing the intimacies of their own silences, I have four core principles posted on the board that sits in the front of my class, which every student signs
at the beginning of the year: read critically, write consciously, speak clearly, tell your truth.

7
00:01:14,408 --> 00:01:18,871
And I find myself thinking a lot about that last point, tell your truth.

8
00:01:18,871 --> 00:01:28,848
And I realized that if I was going to ask my students to speak up, I was going to have to tell my truth and be honest with them about the times where I failed to do so.

9
00:01:28,848 --> 00:01:44,479
So I tell them that growing up, as a kid in a Catholic family in New Orleans, during Lent I was always taught that the most meaningful thing one could do was to give something up, sacrifice something you typically indulge in to prove to God you understand his sanctity.

10
00:01:44,479 --> 00:01:50,183
I've given up soda, McDonald's, French fries, French kisses, and everything in between.

11
00:01:50,183 --> 00:01:54,071
But one year, I gave up speaking.

12
00:01:54,071 --> 00:02:03,286
I figured the most valuable thing I could sacrifice was my own voice, but it was like I hadn't realized that I had given that up a long time ago.

13
00:02:03,286 --> 00:02:23,167
I spent so much of my life telling people the things they wanted to hear instead of the things they needed to, told myself I wasn't meant to be anyone's conscience because I still had to figure out being my own, so sometimes I just wouldn't say anything, appeasing ignorance with my silence, unaware that validation doesn't need words to endorse its existence.

14
00:02:23,167 --> 00:02:29,000
When Christian was beat up for being gay, I put my hands in my pocket and walked with my head
down as if I didn't even notice.

15
00:02:29,000 --> 00:02:39,502
I couldn't use my locker for weeks
because the bolt on the lock reminded me of the one I had put on my lips when the homeless man on the corner looked at me with eyes up merely searching for an affirmation that he was worth seeing.

16
00:02:39,502 --> 00:02:43,170
I was more concerned with
touching the screen on my Apple than actually feeding him one.

17
00:02:43,170 --> 00:02:46,049
When the woman at the fundraising gala said "I'm so proud of you.

18
00:02:46,049 --> 00:02:53,699
It must be so hard teaching
those poor, unintelligent kids," I bit my lip, because apparently
we needed her money more than my students needed their dignity.

19
00:02:53,699 --> 00:03:02,878
We spend so much time listening to the things people are saying that we rarely pay attention to the things they don't.

20
00:03:02,878 --> 00:03:06,139
Silence is the residue of fear.

21
00:03:06,139 --> 00:03:09,615
It is feeling your flaws gut-wrench guillotine your tongue.

22
00:03:09,615 --> 00:03:13,429
It is the air retreating from your chest because it doesn't feel safe in your lungs.

23
00:03:13,429 --> 00:03:15,186
Silence is Rwandan genocide.

24
00:03:15,186 --> 00:03:16,423
 Silence is Katrina.

25
00:03:16,553 --> 00:03:19,661
It is what you hear when there
aren't enough body bags left.

26
00:03:19,661 --> 00:03:22,062
It is the sound after the noose is already tied.

27
00:03:22,062 --> 00:03:22,870
It is charring.

28
00:03:22,870 --> 00:03:23,620
 It is chains.

29
00:03:23,620 --> 00:03:24,543
 It is privilege.

30
00:03:24,543 --> 00:03:25,178
 It is pain.

31
00:03:25,409 --> 00:03:28,897
There is no time to pick your battles when your battles have already picked you.

32
00:03:28,897 --> 00:03:31,960
I will not let silence wrap itself around my indecision.

33
00:03:31,960 --> 00:03:36,287
I will tell Christian that he is a lion, a sanctuary of bravery and brilliance.

34
00:03:36,287 --> 00:03:42,340
I will ask that homeless man what his name is and how his day was, because sometimes all people want to be is human.

35
00:03:42,340 --> 00:03:51,665
I will tell that woman that my students can talk about transcendentalism like their last name was Thoreau, and just because you watched
one episode of "The Wire" doesn't mean you know anything about my kids.

36
00:03:51,665 --> 00:04:03,825
So this year, instead of giving something up, I will live every day as if there were a microphone tucked under my tongue, a stage on the underside of my inhibition.

37
00:04:03,825 --> 00:04:10,207
Because who has to have a soapbox when all you've ever needed is your voice?

38
00:04:10,207 --> 00:04:12,712
Thank you.

39
00:04:12,712 --> 00:00:00,000
(Applause)

Answer 2

它可能不是你想要的，而是计算时间，为什么不直接从字幕文件中取出它们呢？

我以此为例进行了模拟。从长远来看，它并不完美，但它可能会有所帮助。

import re

#Pre-process file to remove blank lines, line numbers and timestamp --> chars
with open('video.srt','r') as f:
    lines = f.readlines()
with open('video.tmp','w') as f:
    for line in lines:
        line = line.strip()
        if line.strip():
            if line.strip().isnumeric():
                continue
            else:
                line = line.replace(' --> ', ' ')
                line = line+" "
                f.write(line)

# Process pre-processed file
with open('video.tmp','r') as f:
    lines = f.readlines()

outfile = open('new_video.srt','w')
idx = 0

# Define the regex options we will need

#regex to look for the time stamps in each sentence using the first and last only
timestamps = re.compile('\d{1,2}(?::\d{2}){1,2}(?:,)\d{3}')

#regex to remove html tags from length calculations
tags = re.compile(r'<.*?>')

#re.split('([^\s\0-9]\.)',a)
# This is to cope with text that contains mathematical, chemical formulae, ip addresses etc
# where "." does not mean full-stop (end of sentence)
# This is used to split on a "." only if it is NOT preceded by space or a number
# this should catch most things but will fail to split the sentence if it genuinely
# ends with a number followed by a full-stop.
end_of_sentence = re.compile(r'([^\s\0-9]\.)')

#sentences = str(lines).split('.')
sentences = re.split(end_of_sentence,str(lines))

# Because the sentences where split on "x." we now have to add that back
# so we concatenate every other list item with the previous one.
idx = 0
joined =[]
while idx < (len(sentences) -1) :
    joined.append(sentences[idx]+sentences[idx+1])
    idx += 2
sentences = joined

previous_timings =["00:00:00,000","00:00:00,000"]
previous_sentence = ""

#Dictionary of timestamps that will require post-processing
registry = {}

loop = 0
for sentence in sentences:
    print(sentence)
    timings = timestamps.findall(sentence)
    idx+=1
    outfile.write(str(idx)+"\n")
    if timings:
        #There are timestamps in the sentence
        previous_timings = timings
        loop = 0
        start_time = timings[0]
        end_time = timings[-1]
        # Revert list item to a string
        sentence = ''.join(sentence)
        # Remove timestamps from the text
        sentence = ''.join(re.sub(timestamps,' ', sentence))
        # Get rid of multiple spaces and \ characters
        sentence = '  '.join(sentence.split())
        sentence = sentence.replace('  ', ' ')
        sentence = sentence.replace("\\'", "'")
        previous_sentence = sentence
        print("Starts at", start_time)
        print(sentence)
        print("Ends at", end_time,'\n')
        outfile.write(start_time+" --> "+end_time+"\n")
        outfile.write(sentence+"\n\n")

    else:
        # There are no timestamps in the sentence therefore this must
        # be a separate sentence cut adrift from an existing timestamp
        # We will have to estimate its start and end times using data
        # from the last time stamp we know of
        start_time = previous_timings[0]
        reg_end_time = previous_timings[-1]

        # Convert timestamp to  seconds
        h,m,s,milli = re.split(':|,',start_time)
        s_time = (3600*int(h))+(60*int(m))+int(s)+(int(milli)/1000)

        # Guess the timing for the previous sentence and add it
        # but only for the first adrift sentence as the start time will be adjusted
        # This number may well vary depending on the cadence of the speaker
        if loop == 0:
            registry[reg_end_time] = reg_end_time
            #s_time += 0.06 * len(previous_sentence)
            s_time += 0.06 * len(tags.sub('',previous_sentence))
        # Guess the end time
        e_time = s_time + (0.06 * len(tags.sub('',previous_sentence)))

        # Convert start to a timestamp
        s,milli = divmod(s_time,1)
        m,s = divmod(int(s),60)
        h,m = divmod(m,60)
        start_time = "{:02d}:{:02d}:{:02d},{:03d}".format(h,m,s,round(milli*1000))

        # Convert end to a timestamp
        s,milli = divmod(e_time,1)
        m,s = divmod(int(s),60)
        h,m = divmod(m,60)
        end_time = "{:02d}:{:02d}:{:02d},{:03d}".format(h,m,s,round(milli*1000))

        #Register new end time for previous sentence
        if loop == 0:
            loop = 1
            registry[reg_end_time] = start_time

        print("Starts at", start_time)
        print(sentence)
        print("Ends at", end_time,'\n')
        outfile.write(start_time+" --> "+end_time+"\n")
        outfile.write(sentence+"\n\n")
        try:
            # re-set the previous start time in case the following sentence
            # was cut adrift from its time stamp as well
            previous_timings[0] = end_time
        except:
            pass
outfile.close()

#Post processing
if registry:
    outfile = open('new_video.srt','r')
    text = outfile.read()
    new_text = text
    # Run through registered end times and replace them
    # if not the video player will not display the subtitles
    # correctly because they overlap in time
    for key, end in registry.items():
        new_text = new_text.replace(key, end, 1)
        print("replacing", key, "with", end)
    outfile.close()
    outfile = open('new_video.srt','w')
    outfile.write(new_text)
    outfile.close()

编辑：令人高兴的是，我坚持使用这段代码，因为我对这个问题很感兴趣。

虽然我很欣赏它是hackey，并且没有使用re字幕模块，但我相信，在这种情况下，它做得很好。

我已经注释了编辑过的代码，所以希望它会清楚我在做什么以及为什么。

regx正在查找时间戳模式0:00:0,000，00:00:00,000，0:00:00,000等。

\d{1,2}(?::\d{2}){1,2}(?:,)\d{3}

1或2个小数，后跟：+2个小数，后跟：+1或2个小数，后跟3个小数

如果一个连接的句子中有多个开始和结束时间，对于整个句子，我们只需要第一个句子的开始时间和最后一个句子的结束时间。我希望这是很清楚的。

编辑2这个版本处理数学和化学公式中的句号，加上ip数字等。基本上，句号不意味着句号的地方。

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