python调用百度语音识别实现大音频文件语音识别功能_Python

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）。
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									# coding: utf-8

									import json

									import time

									import base64

									from inc import rtysdb

									import urllib2

									import requests

									import os

									import uuid

									from 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服务器之家。
原文链接：https://blog.csdn.net/septwolves2015/article/details/78554524
python调用百度语音识别实现大音频文件语音识别功能

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