通过百度MrcpServer实现简单的呼叫对话机器人。
一、参考百度AI接入指南，创建应用，获取AppID、API Key、Secret Key，用于后续配置使用
https://ai.baidu.com/ai-doc/REFERENCE/Ck3dwjgn3
二、下载MrcpServer安装包
sdk_asr_MRCPServer-20200609.tar.gz
https://ai.baidu.com/ai-doc/SPEECH/7kaxz0h2z
https://ai.baidu.com/download?sdkId=111
wget https://platform.bj.bcebos.com/sdk%2FasMRCPServer-20200609.tar.gz
三、解压
sdk_asr_MRCPServer-20200609.tar.gz文件。会生成个MRCPServer文件夹。
tar -xvf sdk%2Fasr%2FMRCPServer-20200609.tar.gz
四、.安装百度MrcpServer
cd MRCPServer/
sh ./bootstrap.sh
ll /opt/compiler/
total 4
drwxrwxr-x 3 3308 3308 4096 Jun 9 2020 gcc-8.2
五、配置Mrcp
1>配置ASR，为FreeSWITCH提供语音识别服务。
mrcp-server/conf/mrcp-asr.conf
更改AUTH_APPID和AUTH_APPKEY为从百度官方获取的APPID和API Key的值
2>配置TTS，为FreeSWITCH提供语音合成服务。
配置文件为：
mrcp-server/conf/mrcp-proxy.conf
更改AUTH_APPID和AUTH_APPKEY为从百度官方获取的APPID和API Key的值
3>配置MrcpServer的SIP服务端，为FreeSWITCH的MrcpClient提供SIP服务。
mrcp-server/conf/unimrcpserver.xml
4>启动MrcpServer，无报错即正常。
cd mrcp-server/
./bin/unimrcpserver -r . &
5>FreeSWITCH使用百度的MrcpServer需要用到grammar.xml这个语法文件。
cp /MRCPServer/mrcp-server/data/grammar.xml /etc/freeswitch/grammar/baidu.gram
六、FreeSWITCH配置
vim /etc/freeswitch/conf/mrcp_profiles/baiduserver.xml
<include>
<!-- 后面我们使用该配置文件，均使用 name 作为唯一标识，而不是文件名 -->
<profile name="baiduserver" version="2">
<!-- Mrcp Server 地址 -->
<!-- Mrcp Server 地址和FreeSWITCH如果不在同一个服务器,请酌情修改 -->
<param name="server-ip" value="127.0.0.1"/>
<!-- Mrcp Server 端口号 -->
<param name="server-port" value="6060"/>
<param name="resource-location" value=""/>
<!-- FreeSWITCH的Mrcp Clent的ip/port/transfer/rtp-ip/rtp-port等信息 -->
<!-- Mrcp Server 地址和FreeSWITCH如果不在同一个服务器,请酌情修改client-ip/rtp-ip，以便能连接到Mrcp Server -->
<param name="client-ip" value="127.0.0.1" />
<param name="client-port" value="6666"/>
<param name="sip-transport" value="udp"/>
<param name="rtp-ip" value="127.0.0.1"/>
<param name="rtp-port-min" value="21000"/>
<param name="rtp-port-max" value="22000"/>
<param name="speechsynth" value="speechsynthesizer"/>
<param name="speechrecog" value="speechrecognizer"/>
<param name="codecs" value="PCMU PCMA L16/96/8000"/>
<!-- Add any default MRCP params for SPEAK requests here -->
<synthparams>
</synthparams>
<!-- Add any default MRCP params for RECOGNIZE requests here -->
<recogparams>
<!--param name="start-input-timers" value="false"/-->
</recogparams>
</profile>
</include>
vim /etc/freeswitch/conf/autoload_configs/unimrcp.conf.xml
<configuration name="unimrcp.conf" description="UniMRCP Client">
<settings>
<param name="default-tts-profile" value="baiduserver"/>
<param name="default-asr-profile" value="baiduserver"/>
<param name="log-level" value="DEBUG"/>
<param name="enable-profile-events" value="false"/>
<param name="max-connection-count" value="100"/>
<param name="offer-new-connection" value="1"/>
<param name="request-timeout" value="3000"/>
</settings>
<profiles>
<X-PRE-PROCESS cmd="include" data="../mrcp_profiles/*.xml"/>
</profiles>
</configuration>
七、测试
<!-- 百度 unimrcp server asr 测试 Python/ target=_blank class=infotextkey>Python版 -->
<!-- play_and_detect_speech -->
<extension name="asr-play-and-detect-speech">
<condition field="destination_number" expression="^88994$">
<action application="sleep" data="1000"/>
<action application="answer" />
<action application="python" data="test"/>
</condition>
</extension>
import os
import freeswitch
from freeswitch import *
import sys
import json
import tempfile
# import requests
import xml.etree.ElementTree as ET
import freeswitch as fs
from freeswitch import *
from xml.dom.minidom import parseString
import random
import requests
###########百度UNIT3.0聊天###########
client_id = "ADIB9GGUGzYNpL**************"
client_key = "eOu8qYRU5sogDKMKVkMYheXV**********"
user_id = "88888" # 默认user_id都为88888
def handler(session, args):
session.answer()
session.sleep(1000)
session.execute("speak", "unimrcp:baiduserver||" + "我是你的智能小卓子,有什么可以帮助你的?")
tryagain = 0
while session.ready():
session.execute("play_and_detect_speech",
"silence_stream://1000 detect:unimrcp:baiduserver {start-input-timers=false,no-input-timeout=60000,input-timeout=60000,recognition-timeout=60000}builtin:grammar/baidu")
asr_result = session.getVariable('detect_speech_result')
if asr_result is None:
tryagain = 0
else:
try:
freeswitch.consoleLog("CRIT", "n====================n'" + asr_result + "'====================n")
#语音转文字
guest_text = asr2text(asr_result)
# freeswitch.consoleLog("CRIT", "----------------结果识别-------------------:'" + text + "'n")
tryagain = 1
#对接机器人
bot_text=bot_chat(guest_text, user_id, client_id, client_key)
session.execute("speak", "unimrcp:baiduserver||" + bot_text)
except Exception as e:
fs.consoleLog('CRIT', '>>> ASR result parse failed n%s' % e)
continue
session.sleep(1000)
session.hangup()
def asr2text(text):
xml_dom = parseString(text)
collection = xml_dom.documentElement
returnInfo = collection.getElementsByTagName("input")
guest_text =returnInfo[0].firstChild.data
return guest_text
def bot_chat(chat_input, user_id, client_id, client_secret):
# 设置默认回复
chat_reply = "不好意思，我正在学习中，随后回复你"
# 固定的url格式
url = "https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=%s&client_secret=%s" % (
client_id, client_secret)
res = requests.post(url)
access_token = json.loads(res.text)["access_token"]
unit_chatbot_url = "https://aip.baidubce.com/rpc/2.0/unit/service/v3/chat?access_token=" + access_token
# 拼装聊天接口对应请求
post_data = {
"version": "3.0",
"service_id": "S75157",
"session_id": "",
"log_id": str(random.random()),
"skill_ids":["1237888","1237895"],
"request":
{
"terminal_id": user_id,
"query": chat_input
}
}
# 将聊天接口对应请求数据转为json数据
res = requests.post(url=unit_chatbot_url, json=post_data)
# 获取聊天接口返回数据
unit_chat_obj = json.loads(res.text)
if unit_chat_obj["error_code"] != 0:
return chat_reply+'('+unit_chat_obj["error_msg"]+')'
unit_chat_response_reply = unit_chat_obj['result']['responses'][0]['actions'][0]['say']
return unit_chat_response_reply
