如何用Python结合百度语音识别和图灵对话系统？

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示例如下，上传后只需声音超过2000，即可开始录音5秒，录音上传百度识别人工智能，并返回结果文字输出，持续等待，声音是否超过2000，没有则等待。

图例如下

github.com/Dongvdong/python_Smartvoice

• 上电后，只要周围声音超过 2000，开始录音5S
• 录音上传百度识别，并返回结果文字输出
• 继续等待，周围声音是否超过2000，没有就等待。
• 点用电脑API语音交互

代码如下

# -*- coding: utf-8 -*- # 树莓派 from pyaudio import PyAudio, paInt16 import numpy as np from datetime import datetime import wave import time import requests#导入requests库 import urllib, urllib.request, pycurl import base64 import json import os import sys from imp import reload # 调用电脑API生成语音交互 import speech import win32api import os import sys import time import win32con reload(sys) #sys.setdefaultencoding( "utf-8" ) #一些全局变量 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'#防止中文乱码 return html.text def get_token(): apiKey = "AxXDYEN27Ks9XHocsGmCEdPm" secretKey = "61cd52759f4d704d91c155a22ff7183d" auth_url = "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'#防止中文乱码 #print (res.text) return json.loads(res.text)['access_token'] def dump_res(buf):#输出百度语音识别的结果 global duihua #print ("字符串类型") #print (buf) a = eval(buf) #print (type(a)) if a['err_msg']=='success.': #print (a['result'][0]）#终于搞定了，在这里可以输出，返回的语句 duihua = a['result'][0] print ("我："+duihua) def use_cloud(token):#进行合成 fp = wave.open(filename, 'rb') nf = fp.getnframes() f_len = nf * 2 audio_data = fp.readframes(nf) cuid = "9120612" #产品id srv_url = 'vop.baidu.com/server_api' + '?cuid=' + cuid + '&token=' + token www.tuling123.com/openapi/api?key=' + key + '&info=' while(True): # 读入NUM_SAMPLES个取样 string_audio_data = stream.read(NUM_SAMPLES,False); # 将读入的数据转换为数组 audio_data = np.fromstring(string_audio_data, dtype=np.short) # 计算大于LEVEL的取样的个数 large_sample_count = np.sum( audio_data > LEVEL ) temp = np.max(audio_data) if temp > 2000 and t == 0: t = 1#开启录音 print ("---------主人我在听你说！（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，准备结束") # 如果个数大于COUNT_NUM，则至少保存SAVE_LENGTH个块 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: # 将要保存的数据存放到save_buffer中 save_buffer.append(string_audio_data ) else: # 将save_buffer中的数据写入WAV文件，WAV文件的文件名是保存的时刻 #if time_flag: if len(save_buffer) > 0 or time_flag: #filename = datetime.now().strftime("%Y-%m-%d_%H_%M_%S") + ".wav"#原本是用时间做名字 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, "保存成功正在进行语音识别") 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 # 将Unicode转化为普通Python字符串："encode" utf8string = unicodestring.encode("utf-8") print ("科塔娜："+str(a)) # 电脑说话 speech.say(str(a)) url = "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))

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