python调用百度语音识别实现大音频文件语音识别功能

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-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])

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