利用免费的百度语音及合成服务，百度机器人聊天服务，我们就可以用树莓派搭建自己的语音机器人
ps：本来想用图灵机器人，但是最近貌似收费，因此还是换成百度。有条件的可以用图灵机器人百度机器人有点傻。
基本硬件：树莓派3B,麦克风（不需要带声卡，淘宝10块钱的就可以），有线音响.
基本框图
翻译文字代码：
# coding=utf-8import sysimport jsonimport base64import timeIS_PY3 = sys.version_info.major == 3if IS_PY3:from urllib.request import urlopenfrom urllib.request import Requestfrom urllib.error import URLErrorfrom urllib.parse import urlencodetimer = time.perf_counterelse:from urllib2 import urlopenfrom urllib2 import Requestfrom urllib2 import URLErrorfrom urllib import urlencodeif sys.platform == "win32":timer = time.clockelse:# On most other platforms the best timer is time.time()timer = time.timeAPI_KEY = '***'SECRET_KEY = '***'# 需要识别的文件AUDIO_FILE = 'record_voice.wav' # 只支持 pcm/wav/amr 格式，极速版额外支持m4a 格式# 文件格式FORMAT = AUDIO_FILE[-3:] # 文件后缀只支持 pcm/wav/amr 格式，极速版额外支持m4a 格式CUID = '123456PYTHON'# 采样率RATE = 16000 # 固定值# 普通版DEV_PID = 1537 # 1537 表示识别普通话，使用输入法模型。根据文档填写PID，选择语言及识别模型ASR_URL = '/server_api'SCOPE = 'audio_voice_assistant_get' # 有此scope表示有asr能力，没有请在网页里勾选，非常旧的应用可能没有#测试自训练平台需要打开以下信息， 自训练平台模型上线后，您会看见 第二步：“”获取专属模型参数pid:8001，modelid:1234”，按照这个信息获取 dev_pid=8001，lm_id=1234# DEV_PID = 8001 ; # LM_ID = 1234 ;# 极速版 打开注释的话请填写自己申请的appkey appSecret ，并在网页中开通极速版（开通后可能会收费）# DEV_PID = 80001# ASR_URL = '/pro_api'# SCOPE = 'brain_enhanced_asr' # 有此scope表示有极速版能力，没有请在网页里开通极速版# 忽略scope检查，非常旧的应用可能没有# SCOPE = Falseclass DemoError(Exception):pass""" TOKEN start """TOKEN_URL = '/oauth/2.0/token'def fetch_token():params = {'grant_type': 'client_credentials','client_id': API_KEY,'client_secret': SECRET_KEY}post_data = urlencode(params)if (IS_PY3):post_data = post_data.encode( 'utf-8')req = Request(TOKEN_URL, post_data)try:f = urlopen(req)result_str = f.read()except URLError as err:print('token http response http code : ' + str(err.code))result_str = err.read()if (IS_PY3):result_str = result_str.decode()print(result_str)result = json.loads(result_str)print(result)if ('access_token' in result.keys() and 'scope' in result.keys()):print(SCOPE)if SCOPE and (not SCOPE in result['scope'].split(' ')): # SCOPE = False 忽略检查raise DemoError('scope is not correct')print('SUCCESS WITH TOKEN: %s EXPIRES IN SECONDS: %s' % (result['access_token'], result['expires_in']))return result['access_token']else:raise DemoError('MAYBE API_KEY or SECRET_KEY not correct: access_token or scope not found in token response')def translation_text():token = fetch_token()speech_data = []with open(AUDIO_FILE, 'rb') as speech_file:speech_data = speech_file.read()length = len(speech_data)if length == 0:raise DemoError('file %s length read 0 bytes' % AUDIO_FILE)speech = base64.b64encode(speech_data)if (IS_PY3):speech = str(speech, 'utf-8')params = {'dev_pid': DEV_PID,#"lm_id" : LM_ID, #测试自训练平台开启此项'format': FORMAT,'rate': RATE,'token': token,'cuid': CUID,'channel': 1,'speech': speech,'len': length}post_data = json.dumps(params, sort_keys=False)# print post_datareq = Request(ASR_URL, post_data.encode('utf-8'))req.add_header('Content-Type', 'application/json')try:begin = timer()f = urlopen(req)result_str = f.read()print ("Request time cost %f" % (timer() - begin))except URLError as err:print('asr http response http code : ' + str(err.code))result_str = err.read()if (IS_PY3):result_str= str(result_str, 'utf-8')a=json.loads(result_str)b=a['result']print(a['result'])with open("result.txt","w") as of:of.write(result_str)return b""" TOKEN end """if __name__ == '__main__':translation_text()
语音输出代码：
# coding=utf-8from aip import AipSpeechimport osimport sys#import importlib # reload(sys)""" 你的 APPID AK SK """APP_ID = '25326941'API_KEY = 'U9B7tKwMqwxhqvZ9oAgUEvD3'SECRET_KEY = 'rpr1q0gC7ELOUIXIfXPHj4ATHzZnfUji'def synath(speech):client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)result = client.synthesis(speech)# 识别正确返回语音二进制 错误则返回dict 参照下面错误码if not isinstance(result, dict):with open('au.mp3', 'wb') as f:f.write(result)if __name__ == '__main__':APP_ID = '25326941'API_KEY = 'U9B7tKwMqwxhqvZ9oAgUEvD3'SECRET_KEY = 'rpr1q0gC7ELOUIXIfXPHj4ATHzZnfUji'synath('zjk')
遍利字典
#!/usr/bin/env python3# -*- coding: utf-8 -*-'遍历字典，查找键值'# get_value.py 文件内容def get_target_value(key, dic, tmp_list):""":param key: 目标key值:param dic: JSON数据:param tmp_list: 用于存储获取的数据:return: list"""if not isinstance(dic, dict) or not isinstance(tmp_list, list): # 对传入数据进行格式校验return 'argv[1] not an dict or argv[-1] not an list 'if key in dic.keys():tmp_list.append(dic[key]) # 传入数据存在则存入tmp_listfor value in dic.values(): # 传入数据不符合则对其value值进行遍历if isinstance(value, dict):get_target_value(key, value, tmp_list) # 传入数据的value值是字典，则直接调用自身elif isinstance(value, (list, tuple)):_get_value(key, value, tmp_list) # 传入数据的value值是列表或者元组，则调用_get_valuereturn tmp_listdef _get_value(key, val, tmp_list):for val_ in val:if isinstance(val_, dict): get_target_value(key, val_, tmp_list) # 传入数据的value值是字典，则调用get_target_valueelif isinstance(val_, (list, tuple)):_get_value(key, val_, tmp_list) # 传入数据的value值是列表或者元组，则调用自身
主函数
import apiimport recordimport sysimport osimport speechimport datetimeimport requestsimport respondimport get_valueimport jsonclient_id = 'MWgD1pMT99mHuPk2wknoeMCf'client_secret = 'Nfrg6LcuuTvArQRSQp5X6gjhU0fxHbI5'print('start,record')pathename= record.record()print('beginning change')result=api.k()r=respond.get_token(client_id,client_secret)url = '/rpc/2.0/unit/service/v3/chat?access_token=' + access_tokenpost_data ={"version":"3.0","service_id":"S62437","session_id":"","log_id":"7758521","request":{"terminal_id":"88888","query":""}}post_data["request"]["query"]=str(result)print(type(result),result)encoded_data = json.dumps(post_data).encode('utf-8') headers = {'content-type': 'application'}responses = requests.post(url, encoded_data, headers=headers)f_zero_dict=responses.json()f=get_value.get_target_value("say",f_zero_dict,[])speech.synath(f[0])os.system('mplayer au.mp3')if responses:print(f[0])
百度的语音识别文字精准度很高，但是机器人有点傻，可以训练 ,有条件可以用图灵。
实例测试
