python-视频声音根据语音识别自动转为带时间的srt字幕文件

2021-05-19 17:17:21 浏览数 (1)

文章目录

  • 问题
  • 解决
    • 截图
    • srt格式原理
    • 识别语音的讯飞接口调用函数
    • 处理结果,得到字符
    • 列表合成字典

问题

讯飞文字转写长语音只有5h免费,想要体验50000分钟白嫖的,看我另一篇文章 最近在看一些教程,发现没有字幕,网络上也没有匹配的,看着很别扭 因此我使用au处理了视频,得到了视频声音,wav格式,20多分钟长度 然后使用讯飞的语音识别接口识别了下,得到了每句话识别的文字和视频对应的时间 然后按照srt格式对其进行了输出 这样就能给那些没有字幕的视频自动添加字幕了 我的需求大致满足了,记录一下。

解决

截图

视频字幕效果

字幕是语音识别自动添加的 代码框输出格式

最后会生成srt字幕文件

srt格式原理

如图,第一个是序号,第二个是字幕显示时间段,精确到微秒,底下就是文字,中英文随意 字幕序号一般是顺序增加的,但是对视频没用,主要还是为了方便翻译人员翻译和观看,但是不可或缺,这是必要的格式 更加详细的看这个链接,这是我查的资料https://www.cnblogs.com/tocy/p/subtitle-format-srt.html

识别语音的讯飞接口调用函数

这个直接复制粘贴就行,只是一个调用的函数,非常通用,下面的另外一个函数是调用他的,位于同一个文件夹下的两个py文件 voice_get_text.py

代码语言:javascript复制
# -*- coding: utf-8 -*-
#
#
# 非实时转写调用demo

import base64
import hashlib
import hmac
import json
import os
import time

import requests

lfasr_host = 'http://raasr.xfyun.cn/api'

# 请求的接口名
api_prepare = '/prepare'
api_upload = '/upload'
api_merge = '/merge'
api_get_progress = '/getProgress'
api_get_result = '/getResult'
# 文件分片大小10M
file_piece_sice = 10485760

# ——————————————————转写可配置参数————————————————
# 参数可在官网界面(https://doc.xfyun.cn/rest_api/语音转写.html)查看,根据需求可自行在gene_params方法里添加修改
# 转写类型
lfasr_type = 0
# 是否开启分词
has_participle = 'false'
has_seperate = 'true'
# 多候选词个数
max_alternatives = 0
# 子用户标识
suid = ''


class SliceIdGenerator:
    """slice id生成器"""

    def __init__(self):
        self.__ch = 'aaaaaaaaa`'

    def getNextSliceId(self):
        ch = self.__ch
        j = len(ch) - 1
        while j >= 0:
            cj = ch[j]
            if cj != 'z':
                ch = ch[:j]   chr(ord(cj)   1)   ch[j   1:]
                break
            else:
                ch = ch[:j]   'a'   ch[j   1:]
                j = j - 1
        self.__ch = ch
        return self.__ch


class RequestApi(object):
    def __init__(self, appid, secret_key, upload_file_path):
        self.appid = appid
        self.secret_key = secret_key
        self.upload_file_path = upload_file_path

    # 根据不同的apiname生成不同的参数,本示例中未使用全部参数您可在官网(https://doc.xfyun.cn/rest_api/语音转写.html)查看后选择适合业务场景的进行更换
    def gene_params(self, apiname, taskid=None, slice_id=None):
        appid = self.appid
        secret_key = self.secret_key
        upload_file_path = self.upload_file_path
        ts = str(int(time.time()))
        m2 = hashlib.md5()
        m2.update((appid   ts).encode('utf-8'))
        md5 = m2.hexdigest()
        md5 = bytes(md5, encoding='utf-8')
        # 以secret_key为key, 上面的md5为msg, 使用hashlib.sha1加密结果为signa
        signa = hmac.new(secret_key.encode('utf-8'), md5, hashlib.sha1).digest()
        signa = base64.b64encode(signa)
        signa = str(signa, 'utf-8')
        file_len = os.path.getsize(upload_file_path)
        file_name = os.path.basename(upload_file_path)
        param_dict = {
   }

        if apiname == api_prepare:
            # slice_num是指分片数量,如果您使用的音频都是较短音频也可以不分片,直接将slice_num指定为1即可
            slice_num = int(file_len / file_piece_sice)   (0 if (file_len % file_piece_sice == 0) else 1)
            param_dict['app_id'] = appid
            param_dict['signa'] = signa
            param_dict['ts'] = ts
            param_dict['file_len'] = str(file_len)
            param_dict['file_name'] = file_name
            param_dict['slice_num'] = str(slice_num)
        elif apiname == api_upload:
            param_dict['app_id'] = appid
            param_dict['signa'] = signa
            param_dict['ts'] = ts
            param_dict['task_id'] = taskid
            param_dict['slice_id'] = slice_id
        elif apiname == api_merge:
            param_dict['app_id'] = appid
            param_dict['signa'] = signa
            param_dict['ts'] = ts
            param_dict['task_id'] = taskid
            param_dict['file_name'] = file_name
        elif apiname == api_get_progress or apiname == api_get_result:
            param_dict['app_id'] = appid
            param_dict['signa'] = signa
            param_dict['ts'] = ts
            param_dict['task_id'] = taskid
        return param_dict

    # 请求和结果解析,结果中各个字段的含义可参考:https://doc.xfyun.cn/rest_api/语音转写.html
    def gene_request(self, apiname, data, files=None, headers=None):
        response = requests.post(lfasr_host   apiname, data=data, files=files, headers=headers)
        result = json.loads(response.text)
        if result["ok"] == 0:
            print("{} success:".format(apiname)   str(result))
            return result
        else:
            print("{} error:".format(apiname)   str(result))
            exit(0)
            return result

    # 预处理
    def prepare_request(self):
        return self.gene_request(apiname=api_prepare,
                                 data=self.gene_params(api_prepare))

    # 上传
    def upload_request(self, taskid, upload_file_path):
        file_object = open(upload_file_path, 'rb')
        try:
            index = 1
            sig = SliceIdGenerator()
            while True:
                content = file_object.read(file_piece_sice)
                if not content or len(content) == 0:
                    break
                files = {
   
                    "filename": self.gene_params(api_upload).get("slice_id"),
                    "content": content
                }
                response = self.gene_request(api_upload,
                                             data=self.gene_params(api_upload, taskid=taskid,
                                                                   slice_id=sig.getNextSliceId()),
                                             files=files)
                if response.get('ok') != 0:
                    # 上传分片失败
                    print('upload slice fail, response: '   str(response))
                    return False
                print('upload slice '   str(index)   ' success')
                index  = 1
        finally:
            'file index:'   str(file_object.tell())
            file_object.close()
        return True

    # 合并
    def merge_request(self, taskid):
        return self.gene_request(api_merge, data=self.gene_params(api_merge, taskid=taskid))

    # 获取进度
    def get_progress_request(self, taskid):
        return self.gene_request(api_get_progress, data=self.gene_params(api_get_progress, taskid=taskid))

    # 获取结果
    def get_result_request(self, taskid):
        return self.gene_request(api_get_result, data=self.gene_params(api_get_result, taskid=taskid))

    def all_api_request(self):
        # 1. 预处理
        pre_result = self.prepare_request()
        taskid = pre_result["data"]
        # 2 . 分片上传
        self.upload_request(taskid=taskid, upload_file_path=self.upload_file_path)
        # 3 . 文件合并
        self.merge_request(taskid=taskid)
        # 4 . 获取任务进度
        while True:
            # 每隔20秒获取一次任务进度
            progress = self.get_progress_request(taskid)
            progress_dic = progress
            if progress_dic['err_no'] != 0 and progress_dic['err_no'] != 26605:
                print('task error: '   progress_dic['failed'])
                return
            else:
                data = progress_dic['data']
                task_status = json.loads(data)
                if task_status['status'] == 9:
                    print('task '   taskid   ' finished')
                    break
                print('The task '   taskid   ' is in processing, task status: '   str(data))

            # 每次获取进度间隔20S
            time.sleep(20)
        # 5 . 获取结果
        aaa=self.get_result_request(taskid=taskid)
        return aaa
        print(aaa)

处理结果,得到字符

放入自己在讯飞申请的语音转文字功能的id与key,执行后会得到一个巨长的声音识别后的dict字符串,自己处理一下变成srt格式就行了。当然这里我写的输出就是srt video_to_txt.py

代码语言:javascript复制
# coding=gbk
import voice_get_text
import datetime
video_path=input("音频路径:").replace("\",'/')
print("开始处理...请等待")
api = voice_get_text.RequestApi(appid="申请的id", secret_key="申请的key",
                             upload_file_path=video_path)
myresult=api.all_api_request()
def get_format_time(time_long):
    def format_number(num):
        if len(str(num))>1:
            return str(num)
        else:
            return "0" str(num)
    myhour=0
    mysecond=int(time_long/1000)
    myminute=0
    mymilsec=0
    if mysecond<1:
        return "00:00:00,%s"%(time_long)
    else:
        if mysecond>60:
            myminute=int(mysecond/60)
            if myminute>60:
                myhour=int(myminute/60)
                myminute=myminute-myhour*60
                mysecond=mysecond-myhour*3600-myminute*60
                mymilsec=time_long-1000*(mysecond myhour*3600 myminute*60)
                return "%s:%s:%s,%s"%(format_number(myhour),format_number(myminute),format_number(mysecond),
                                      format_number(mymilsec))
            else:
                mysecond=int(mysecond-myminute*60)
                mymilsec=time_long-1000*(mysecond myminute*60)
                return "00:%s:%s,%s"%(format_number(myminute),format_number(mysecond),format_number(mymilsec))
        else:
            mymilsec=time_long-mysecond*1000
            return "00:00:%s,%s"%(mysecond,mymilsec)
myresult_str=myresult["data"]
myresult_sp=myresult_str.split("},{")
myresult_sp=myresult_sp[1:-1]
myword=""
flag_num=0
for i in myresult_sp:
    flag_num =1
    print(i)
    word=[]
    key=[]
    a=i.split(",")
    for j in a:
        temp=j.split(":")
        key.append(temp[0][1:-1])
        word.append(temp[1][1:-1])
    get_dic=dict(zip(key,word))
    print(get_dic)
    bg= get_format_time(int(get_dic["bg"]))
    ed= get_format_time(int(get_dic["ed"]))
    real_word=get_dic["onebest"]
    newword=str(flag_num) "n" bg " --> " ed 'n' real_word "nnn"
    myword=myword newword
print(myword)
# myword=video_path.split("/")[-1] "n" myword
nowTime_str = datetime.datetime.strftime(datetime.datetime.now(), '%Y-%m-%d %H-%M-%S')
path_file=r"C:UsersAdministrator.DESKTOP-KMH7HN6Desktopvideo_text%s.srt"%(nowTime_str)
f = open(path_file,'a')
f.write(myword)
f.write('n')
f.close()
print('已经识别完成,见输出目录下的srt文件')
input()

列表合成字典

这个无视即可,随手写的代码

代码语言:javascript复制
# -*- coding: utf-8 -*-
keys = ['a', 'b', 'c']
values = [1, 2, 3]
mydic = dict(zip(keys, values))
print (mydic)

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