這篇文章運用簡單易懂的例子給大家介紹使用python實現百度語音識別和圖靈對話，內容非常詳細，感興趣的小伙伴們可以參考借鑒，希望對大家能有所幫助。

圖例如下

https://github.com/Dongvdong/python_Smartvoice

• 上電后，只要周圍聲音超過 2000，開始錄音5S
• 錄音上傳百度識別，并返回結果文字輸出
• 繼續等待，周圍聲音是否超過2000，沒有就等待。
• 點用電腦API語音交互

代碼如下

# -*- coding: utf-8 -*-
# 樹莓派
from pyaudio import PyAudio, paInt16
import numpy as np
from datetime import datetime
import wave
import time
import requests#導入requests庫
import urllib, urllib.request, pycurl
import base64
import json
import os
import sys
from imp import reload
 
# 調用電腦API生成語音交互
import speech
import win32api
import os
import sys
import time
import win32con
 
 
reload(sys)
 
#sys.setdefaultencoding( "utf-8" )
#一些全局變量
save_count = 0
save_buffer = []
t = 0
sum = 0
time_flag = 0
flag_num = 0
filename = ''
duihua = '1'
def getHtml(url):
  html= requests.get(url)
  # html.encoding = 'utf-8'#防止中文亂碼
  
  return html.text
def get_token():
  apiKey = "AxXDYEN27Ks9XHocsGmCEdPm"
  secretKey = "61cd52759f4d704d91c155a22ff7183d"
  auth_url = "https://openapi.baidu.com/oauth/2.0/token?grant_type=client_credentials&client_id=" + apiKey + "&client_secret=" + secretKey;
  res = requests.get(auth_url)
  #res.encoding = 'utf-8'#防止中文亂碼
  #print (res.text)
  return json.loads(res.text)['access_token']
def dump_res(buf):#輸出百度語音識別的結果
  global duihua
  #print ("字符串類型")
  #print (buf)
  a = eval(buf)
  #print (type(a))
  if a['err_msg']=='success.':
    #print (a['result'][0]）#終于搞定了，在這里可以輸出，返回的語句
    duihua = a['result'][0]
    print ("我："+duihua)
def use_cloud(token):#進行合成
  fp = wave.open(filename, 'rb')
  nf = fp.getnframes()
  f_len = nf * 2
  audio_data = fp.readframes(nf)
  cuid = "9120612" #產品id
  srv_url = 'http://vop.baidu.com/server_api' + '?cuid=' + cuid + '&token=' + token
  http_header = [
    'Content-Type: audio/pcm; rate=8000',
    'Content-Length: %d' % f_len
  ]
  c = pycurl.Curl()
  c.setopt(pycurl.URL, str(srv_url)) #curl doesn't support unicode
  #c.setopt(c.RETURNTRANSFER, 1)
  c.setopt(c.HTTPHEADER, http_header)  #must be list, not dict
  c.setopt(c.POST, 1)
  c.setopt(c.CONNECTTIMEOUT, 30)
  c.setopt(c.TIMEOUT, 30)
  c.setopt(c.WRITEFUNCTION, dump_res)
  c.setopt(c.POSTFIELDS, audio_data)
  c.setopt(c.POSTFIELDSIZE, f_len)
  c.perform() #pycurl.perform() has no return val
# 將data中的數據保存到名為filename的WAV文件中
def save_wave_file(filename, data):
  wf = wave.open(filename, 'wb')
  wf.setnchannels(1)
  wf.setsampwidth(2)
  wf.setframerate(SAMPLING_RATE)
  wf.writeframes(b"".join(data))
  wf.close()
NUM_SAMPLES = 2000    # pyAudio內部緩存的塊的大小
SAMPLING_RATE = 8000  # 取樣頻率
LEVEL = 1500      # 聲音保存的閾值
COUNT_NUM = 20     # NUM_SAMPLES個取樣之內出現COUNT_NUM個大于LEVEL的取樣則記錄聲音
SAVE_LENGTH = 8     # 聲音記錄的最小長度：SAVE_LENGTH * NUM_SAMPLES 個取樣
exception_on_overflow=False
# 開啟聲音輸入ｐｙａｕｄｉｏ對象
pa = PyAudio()
stream = pa.open(format=paInt16, channels=1, rate=SAMPLING_RATE, input=True,
        frames_per_buffer=NUM_SAMPLES)
token = get_token()#獲?。簦铮耄澹?key = '35ff2856b55e4a7f9eeb86e3437e23fe'
api = 'http://www.tuling123.com/openapi/api?key=' + key + '&info='
while(True):
  # 讀入NUM_SAMPLES個取樣
  string_audio_data = stream.read(NUM_SAMPLES,False);
  # 將讀入的數據轉換為數組
  audio_data = np.fromstring(string_audio_data, dtype=np.short)
  # 計算大于LEVEL的取樣的個數
  large_sample_count = np.sum( audio_data > LEVEL )
  temp = np.max(audio_data)
  if temp > 2000 and t == 0:
    t = 1#開啟錄音
    print ("---------主人我在聽你說！（5S）----------")
    begin = time.time()
    # print (temp)
  if t:
    #print (np.max(audio_data))
    if np.max(audio_data)<1000:
      sum += 1
      # print (sum)
    end = time.time()
    if end-begin>5:
      time_flag = 1
      # print ("五秒到了，準備結束")
    # 如果個數大于COUNT_NUM，則至少保存SAVE_LENGTH個塊
    if large_sample_count > COUNT_NUM:
      save_count = SAVE_LENGTH
    else:
      save_count -= 1
    if save_count < 0:
      save_count = 0
    if save_count > 0:
      # 將要保存的數據存放到save_buffer中
      save_buffer.append(string_audio_data )
    else:
      # 將save_buffer中的數據寫入WAV文件，WAV文件的文件名是保存的時刻
      #if time_flag:
      if len(save_buffer) > 0 or time_flag:
        #filename = datetime.now().strftime("%Y-%m-%d_%H_%M_%S") + ".wav"#原本是用時間做名字
        filename = str(flag_num)+".wav"
        flag_num += 1
        save_wave_file(filename, save_buffer)
        save_buffer = []
        t = 0
        sum =0
        time_flag = 0
       # print (filename, "保存成功正在進行語音識別")
        use_cloud(token)
       #  print (duihua)
        info = duihua
        duihua = ""
        
        request = api + str(info)
        response = getHtml(request)
       # print ( "-----1-----")
        dic_json = json.loads(response)
       
        a = dic_json['text']
       
        unicodestring = a
        # 將Unicode轉化為普通Python字符串："encode"
        utf8string = unicodestring.encode("utf-8")
       
        print ("科塔娜："+str(a))
         
        # 電腦說話
        speech.say(str(a))
         
        url = "http://tsn.baidu.com/text2audio?tex="+dic_json['text']+"&lan=zh&per=0&pit=1&spd=7&cuid=7519663&ctp=1&tok=25.41bf315625c68b3e947c49b90788532d.315360000.1798261651.282335-9120612"
        os.system('mpg123 "%s"'%(url))