使用Python和百度语音识别生成视频字幕的实现

脚本专栏 2024/12/24 佚名

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从视频中提取音频

安装 moviepy

pip install moviepy

相关代码：

audio_file = work_path + '\\out.wav'
video = VideoFileClip(video_file)
video.audio.write_audiofile(audio_file,ffmpeg_params=['-ar','16000','-ac','1'])

根据静音对音频分段

使用音频库 pydub，安装：

pip install pydub

第一种方法：

# 这里silence_thresh是认定小于-70dBFS以下的为silence，发现小于 sound.dBFS * 1.3 部分超过 700毫秒，就进行拆分。这样子分割成一段一段的。
sounds = split_on_silence(sound, min_silence_len = 500, silence_thresh= sound.dBFS * 1.3)


sec = 0
for i in range(len(sounds)):
 s = len(sounds[i])
 sec += s
print('split duration is ', sec)
print('dBFS: {0}, max_dBFS: {1}, duration: {2}, split: {3}'.format(round(sound.dBFS,2),round(sound.max_dBFS,2),sound.duration_seconds,len(sounds)))

感觉分割的时间不对，不好定位，我们换一种方法：

# 通过搜索静音的方法将音频分段
# 参考：https://wqian.net/blog/2018/1128-python-pydub-split-mp3-index.html
timestamp_list = detect_nonsilent(sound,500,sound.dBFS*1.3,1)
 
for i in range(len(timestamp_list)):
 d = timestamp_list[i][1] - timestamp_list[i][0]
 print("Section is :", timestamp_list[i], "duration is:", d)
print('dBFS: {0}, max_dBFS: {1}, duration: {2}, split: {3}'.format(round(sound.dBFS,2),round(sound.max_dBFS,2),sound.duration_seconds,len(timestamp_list)))

输出结果如下：

感觉这样好处理一些

使用百度语音识别

现在百度智能云平台创建一个应用，获取 API Key 和 Secret Key：

获取 Access Token

使用百度 AI 产品需要授权，一定量是免费的，生成字幕够用了。

'''
百度智能云获取 Access Token
'''
def fetch_token():
 params = {'grant_type': 'client_credentials',
    'client_id': API_KEY,
    'client_secret': SECRET_KEY}
 post_data = urlencode(params)
 if (IS_PY3):
  post_data = post_data.encode( 'utf-8')
 req = Request(TOKEN_URL, post_data)
 try:
  f = urlopen(req)
  result_str = f.read()
 except URLError as err:
  print('token http response http code : ' + str(err.errno))
  result_str = err.reason
 if (IS_PY3):
  result_str = result_str.decode()


 print(result_str)
 result = json.loads(result_str)
 print(result)
 if ('access_token' in result.keys() and 'scope' in result.keys()):
  print(SCOPE)
  if SCOPE and (not SCOPE in result['scope'].split(' ')): # SCOPE = False 忽略检查
   raise DemoError('scope is not correct')
  print('SUCCESS WITH TOKEN: %s EXPIRES IN SECONDS: %s' % (result['access_token'], result['expires_in']))
  return result['access_token']
 else:
  raise DemoError('MAYBE API_KEY or SECRET_KEY not correct: access_token or scope not found in token response')

使用 Raw 数据进行合成

这里使用百度语音极速版来合成文字，因为官方介绍专有GPU服务集群，识别响应速度较标准版API提升2倍及识别准确率提升15%。适用于近场短语音交互，如手机语音搜索、聊天输入等场景。支持上传完整的录音文件，录音文件时长不超过60秒。实时返回识别结果

def asr_raw(speech_data, token):
 length = len(speech_data)
 if length == 0:
  # raise DemoError('file %s length read 0 bytes' % AUDIO_FILE)
  raise DemoError('file length read 0 bytes')


 params = {'cuid': CUID, 'token': token, 'dev_pid': DEV_PID}
 #测试自训练平台需要打开以下信息
 #params = {'cuid': CUID, 'token': token, 'dev_pid': DEV_PID, 'lm_id' : LM_ID}
 params_query = urlencode(params)


 headers = {
  'Content-Type': 'audio/' + FORMAT + '; rate=' + str(RATE),
  'Content-Length': length
 }


 url = ASR_URL + "" + params_query
 # print post_data
 req = Request(ASR_URL + "" + params_query, speech_data, headers)
 try:
  begin = timer()
  f = urlopen(req)
  result_str = f.read()
  # print("Request time cost %f" % (timer() - begin))
 except URLError as err:
  # print('asr http response http code : ' + str(err.errno))
  result_str = err.reason


 if (IS_PY3):
  result_str = str(result_str, 'utf-8')
 return result_str

生成字幕

字幕格式： https://www.cnblogs.com/tocy/p/subtitle-format-srt.html

生成字幕其实就是语音识别的应用，将识别后的内容按照 srt 字幕格式组装起来就 OK 了。具体字幕格式的内容可以参考上面的文章，代码如下：

idx = 0
for i in range(len(timestamp_list)):
 d = timestamp_list[i][1] - timestamp_list[i][0]
 data = sound[timestamp_list[i][0]:timestamp_list[i][1]].raw_data
 str_rst = asr_raw(data, token)
 result = json.loads(str_rst)
 # print("rst is ", result)
 # print("rst is ", rst['err_no'][0])


 if result['err_no'] == 0:
  text.append('{0}\n{1} --> {2}\n'.format(idx, format_time(timestamp_list[i][0]/ 1000), format_time(timestamp_list[i][1]/ 1000)))
  text.append( result['result'][0])
  text.append('\n')
  idx = idx + 1
  print(format_time(timestamp_list[i][0]/ 1000), "txt is ", result['result'][0])
with open(srt_file,"r+") as f:
 f.writelines(text)

总结

我在视频网站下载了一个视频来作测试，极速模式从速度和识别率来说都是最好的，感觉比网易见外平台还好用。

Python,生成视频字幕,Python,百度语音识别