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python调用百度语音识别实现大音频文件语音识别功能

2020-01-04 14:37:15
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本文为大家分享了python实现大音频文件语音识别功能的具体代码,供大家参考,具体内容如下

实现思路:先用ffmpeg将其他非wav格式的音频转换为wav格式,并转换音频的声道(百度支持声道为1),采样率(值为8000),格式转换完成后,再用ffmpeg将音频切成百度。

支持的时长(30秒和60秒2种,本程序用的是30秒)。

# coding: utf-8import jsonimport timeimport base64from inc import rtysdbimport urllib2import requestsimport osimport uuidfrom inc import db_config  class BaiduRest:  def __init__(self, cu_id, api_key, api_secert):    self.token_url = "https://openapi.baidu.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s"    self.getvoice_url = "http://tsn.baidu.com/text2audio?tex=%s&lan=zh&cuid=%s&ctp=1&tok=%s"    self.upvoice_url = 'http://vop.baidu.com/server_api'     self.cu_id = cu_id    self.get_token(api_key, api_secert)    return   def get_token(self, api_key, api_secert):    token_url = self.token_url % (api_key, api_secert)    r_str = urllib2.urlopen(token_url).read()    token_data = json.loads(r_str)    self.token_str = token_data['access_token']    return True   # 语音合成  def text2audio(self, text, filename):    get_url = self.getvoice_url % (urllib2.quote(text), self.cu_id, self.token_str)    voice_data = urllib2.urlopen(get_url).read()    voice_fp = open(filename, 'wb+')    voice_fp.write(voice_data)    voice_fp.close()    return True   ##语音识别  def audio2text(self, filename):    data = {}    data['format'] = 'wav'    data['rate'] = 8000    data['channel'] = 1    data['cuid'] = self.cu_id    data['token'] = self.token_str     wav_fp = open(filename, 'rb')    voice_data = wav_fp.read()    data['len'] = len(voice_data)    # data['speech'] = base64.b64encode(voice_data).decode('utf-8')    data['speech'] = base64.b64encode(voice_data).replace('/n', '')    # post_data = json.dumps(data)    result = requests.post(self.upvoice_url, json=data, headers={'Content-Type': 'application/json'})    data_result = result.json()    if(data_result['err_msg'] == 'success.'):      return data_result['result'][0]    else:      return False   def test_voice(voice_file):  api_key = "vossGHIgEETS6IMRxBDeahv8"  api_secert = "3c1fe6a6312f41fa21fa2c394dad5510"  bdr = BaiduRest("0-57-7B-9F-1F-A1", api_key, api_secert)   # 生成  #start = time.time()  #bdr.text2audio("你好啊", "out.wav")  #using = time.time() - start  #print using   # 识别  #start = time.time()  result = bdr.audio2text(voice_file)  # result = bdr.audio2text("weather.pcm")  #using = time.time() - start  return result def get_master_audio(check_status='cut_status'):  if check_status == 'cut_status':    sql = "SELECT id,url, time_long,sharps FROM ocenter_recognition WHERE status=0"  elif check_status == 'finished_status':    sql = "SELECT id,url, time_long,sharps FROM ocenter_recognition WHERE finished_status=0"  else:    return False  data = rtysdb.select_data(sql,'more')  if data:    return data  else:    return False  def go_recognize(master_id):  section_path = db_config.SYS_PATH  sql = "SELECT id,rid,url,status FROM ocenter_section WHERE rid=%d AND status=0 order by id asc limit 10" % (master_id)  #print sql  record = rtysdb.select_data(sql,'more')  #print record  if not record:    return False  for rec in record:    #print section_path+'/'+rec[1]    voice_file = section_path+'/'+rec[2]    if not os.path.exists(voice_file):      continue    result = test_voice(voice_file)    print result    exit(0)    if result:      #rtysdb.update_by_pk('ocenter_section',rec[0],{'content':result,'status':1})      sql = "update ocenter_section set content='%s', status='%d' where id=%d" % (result,1,rec[0])      #print sql      rtysdb.do_exec_sql(sql)      parent_content = rtysdb.select_data("SELECT id,content FROM ocenter_recognition WHERE id=%d" % (rec[1]))      #print parent_content      if parent_content:        new_content = parent_content[1]+result        update_content_sql = "update ocenter_recognition set content='%s' where id=%d" % (new_content,rec[1])        rtysdb.do_exec_sql(update_content_sql)    else:      rtysdb.do_exec_sql("update ocenter_section set status='%d' where id=%d" % (result,1,rec[0]))    time.sleep(5)  else:    rtysdb.do_exec_sql("UPDATE ocenter_recognition SET finished_status=1 WHERE id=%d" % (master_id))#对百度语音识别不了的音频文件进行转换def ffmpeg_convert():  section_path = db_config.SYS_PATH  #print section_path  used_audio = get_master_audio('cut_status')  #print used_audio  if used_audio:    for audio in used_audio:      audio_path = section_path+'/'+audio[1]      new_audio = uuid.uuid1()      command_line = "ffmpeg -i "+audio_path +" -ar 8000 -ac 1 -f wav "+section_path+"/Uploads/Convert/convert_" + str(new_audio) +".wav";      #print command_line      os.popen(command_line)      if os.path.exists(section_path+"/Uploads/Convert/convert_" + str(new_audio) +".wav"):        convert_name = "Uploads/Convert/convert_" + str(new_audio) +".wav"        ffmpeg_cut(convert_name,audio[3],audio[0])        sql = "UPDATE ocenter_recognition SET status=1,convert_name='%s' where id=%d" % (convert_name,audio[0])        rtysdb.do_exec_sql(sql)#将大音频文件切成碎片def ffmpeg_cut(convert_name,sharps,master_id):  section_path = db_config.SYS_PATH  if sharps>0:    for i in range(0,sharps):      timeArray = time.localtime(i*30)      h = time.strftime("%H", timeArray)      h = int(h) - 8      h = "0" + str(h)      ms = time.strftime("%M:%S",timeArray)      start_time = h+':'+str(ms)      cut_name = section_path+'/'+convert_name      db_store_name = "Uploads/Section/"+str(uuid.uuid1())+'-'+str(i+1)+".wav"      section_name = section_path+"/"+db_store_name      command_line = "ffmpeg.exe -i "+cut_name+" -vn -acodec copy -ss "+start_time+" -t 00:00:30 "+section_name      #print command_line      os.popen(command_line)      data = {}      data['rid'] = master_id      data['url'] = db_store_name      data['create_time'] = int(time.time())      data['status'] = 0      rtysdb.insert_one('ocenter_section',data) if __name__ == "__main__":  ffmpeg_convert()  audio = get_master_audio('finished_status')  if audio:     for ad in audio:      go_recognize(ad[0])

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持VEVB武林网。


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