python 语音识别机器人控制系统_ROS+科大讯飞语音识别控制机器人

科大讯飞语音识别控制实际机器人运动。

本文将ros与语音识别想结合进行开发。进行以下步骤，

1、创作ros工作空间

2、安装mpalyer播放器

sudo apt-get install mplayer

3、将讯非的语音库动态文件.so文件放到/usr/lib/下

4、ros工程目录src下新建文件xf_asr.cpp 并将以下内容复制进去，appid改成你自己的(官网申请)。

/*

* 语音听写(iFly Auto Transform)技术能够实时地将语音转换成对应的文字。

*/

#include #include #include #include #include "qisr.h"

#include "msp_cmn.h"

#include "msp_errors.h"

#include "speech_recognizer.h"

#include #include "ros/ros.h"

#include "std_msgs/String.h"

#define FRAME_LEN 640

#define BUFFER_SIZE 4096

int wakeupFlag = 0 ;

int resultFlag = 0 ;

static void show_result(char *string, char is_over)

{

resultFlag=1;

printf("\rResult: [ %s ]", string);

if(is_over)

putchar('\n');

}

static char *g_result = NULL;

static unsigned int g_buffersize = BUFFER_SIZE;

void on_result(const char *result, char is_last)

{

if (result) {

size_t left = g_buffersize - 1 - strlen(g_result);

size_t size = strlen(result);

if (left < size) {

g_result = (char*)realloc(g_result, g_buffersize + BUFFER_SIZE);

if (g_result)

g_buffersize += BUFFER_SIZE;

else {

printf("mem alloc failed\n");

return;

}

}

strncat(g_result, result, size);

show_result(g_result, is_last);

}

}

void on_speech_begin()

{

if (g_result)

{

free(g_result);

}

g_result = (char*)malloc(BUFFER_SIZE);

g_buffersize = BUFFER_SIZE;

memset(g_result, 0, g_buffersize);

printf("Start Listening...\n");

}

void on_speech_end(int reason)

{

if (reason == END_REASON_VAD_DETECT)

printf("\nSpeaking done \n");

else

printf("\nRecognizer error %d\n", reason);

}

/* demo recognize the audio from microphone */

static void demo_mic(const char* session_begin_params)

{

int errcode;

int i = 0;

struct speech_rec iat;

struct speech_rec_notifier recnotifier = {

on_result,

on_speech_begin,

on_speech_end

};

errcode = sr_init(&iat, session_begin_params, SR_MIC, &recnotifier);

if (errcode) {

printf("speech recognizer init failed\n");

return;

}

errcode = sr_start_listening(&iat);

if (errcode) {

printf("start listen failed %d\n", errcode);

}

/* demo 10 seconds recording */

while(i++ < 2)

sleep(1);

errcode = sr_stop_listening(&iat);

if (errcode) {

printf("stop listening failed %d\n", errcode);

}

sr_uninit(&iat);

}

/* main thread: start/stop record ; query the result of recgonization.

* record thread: record callback(data write)

* helper thread: ui(keystroke detection)

*/

void WakeUp(const std_msgs::String::ConstPtr& msg)

{

printf("waking up\r\n");

usleep(700*1000);

wakeupFlag=1;

}

int main(int argc, char* argv[])

{

// 初始化ROS

ros::init(argc, argv, "voiceRecognition");

ros::NodeHandle n;

ros::Rate loop_rate(10);

// 声明Publisher和Subscriber

// 订阅唤醒语音识别的信号

ros::Subscriber wakeUpSub = n.subscribe("voiceWakeup", 1000, WakeUp);

// 订阅唤醒语音识别的信号

ros::Publisher voiceWordsPub = n.advertise("voiceWords", 1000);

ROS_INFO("Sleeping...");

int count=0;

while(ros::ok())

{

// 语音识别唤醒

if (wakeupFlag){

ROS_INFO("Wakeup...");

int ret = MSP_SUCCESS;

const char* login_params = "appid = , work_dir = .";

const char* session_begin_params =

"sub = iat, domain = iat, language = zh_cn, "

"accent = mandarin, sample_rate = 16000, "

"result_type = plain, result_encoding = utf8";

ret = MSPLogin(NULL, NULL, login_params);

if(MSP_SUCCESS != ret){

MSPLogout();

printf("MSPLogin failed , Error code %d.\n",ret);

}

printf("Demo recognizing the speech from microphone\n");

printf("Speak in 3 seconds\n");

demo_mic(session_begin_params);

printf("3 sec passed\n");

wakeupFlag=1;

MSPLogout();

}

// 语音识别完成

if(resultFlag)

{

resultFlag=0;

std_msgs::String msg;

msg.data = g_result;

voiceWordsPub.publish(msg);

}

ros::spinOnce();

loop_rate.sleep();

count++;

}

exit:

MSPLogout(); // Logout...

return 0;

}

5、CMakeLists.txt增加以下代码

add_executable(xf_asr src/xf_asr.cpp)

target_link_libraries(xf_asr ${catkin_LIBRARIES} -lmsc -ldl -lpthread -lm -lrt)

add_dependencies(xf_asr xf_voice_generate_messages_cpp)(这句要不要都可以)

6、回到工作空间编译，编译后source一下。此时语音识别已经可以运行，打开新的终端运行roscore。在另一个终端运行asr。

7、添加语音控制的package，新创建一个新的package，在新的src里面创建voice_cmd.cpp。复制一下代码、

#include#include#include#include#include#include//#includeusing namespace std;

ros::Publisher pub;

geometry_msgs::Twist vel_cmd;

pthread_t pth_[5];

void* vel_ctr(void* arg)

{

while(true)

{

pub.publish(vel_cmd);

ros::spinOnce();

sleep(1);

}

return 0;

}

//void callback(const package_name::type_name & msg)

void callback(const std_msgs::String::ConstPtr& msg)

{

cout

string str2 = "11";

string str3 = "22";

string str4 = "33";

string str5 = "44";

string str6 = "55";

//if(str1 == str2)

if(str1.find("前进"))

// if(strstr(&str1, &str2))

{

// cout

pub = n.advertise("/mobile_base/mobile_base_controller/cmd_vel",1000);

ros::Subscriber sub = n.subscribe("/voiceWords",10,callback);

// ros::Subscriber sub = n.subscribe("read",10,callback);

//ros::Publisher pub = n.advertise("/cmd_vel_mux/input/teleop", 10);

cout

8、同理在Cmakelist加上以下：

add_executable(voice_cmd src/voice_cmd.cpp)

target_link_libraries(voice_cmd ${catkin_LIBRARIES} )

add_dependencies(voice_cmd voice_cmd_generate_messages_cpp)

9、回到工作空间编译，运行。

10、运行上面两个模块后再打开一个终端运行rqt_graph查看节点图是否联通。(完)

或者用python去控制机器人运动，订阅asr的内容，

以下是python代码：

#!/usr/bin/env python

# This Python file uses the following encoding: utf-8

import os, sys

import roslib; roslib.load_manifest('pocketsphinx')

import rospy

import math

from geometry_msgs.msg import Twist

from std_msgs.msg import String

class voice_cmd_vel:

def __init__(self):

rospy.on_shutdown(self.cleanup)

self.speed = 0.2

self.msg = Twist()

# publish to cmd_vel, subscribe to speech output

#self.pub_ = rospy.Publisher('/mobile_base/commands/velocity', Twist)

self.pub_ = rospy.Publisher('/mobile_base/mobile_base_controller/cmd_vel', Twist)

rospy.Subscriber('/voiceWords', String, self.speechCb)

r = rospy.Rate(10.0)

while not rospy.is_shutdown():

self.pub_.publish(self.msg)

r.sleep()

def speechCb(self, msg):

rospy.loginfo(msg.data)

#if msg.data.find("full speed") > -1:

if msg.data.find("加速") > -1:

if self.speed == 0.2:

self.msg.linear.x = self.msg.linear.x*2

self.msg.angular.z = self.msg.angular.z*2

self.speed = 0.4

if msg.data.find("减速") > -1:

if self.speed == 0.4:

self.msg.linear.x = self.msg.linear.x/2

self.msg.angular.z = self.msg.angular.z/2

self.speed = 0.2

if msg.data.find("前进") > -1:

#if msg.data.find("forward") > -1:

self.msg.linear.x = self.speed

self.msg.angular.z = 0

elif msg.data.find("左转") > -1:

if self.msg.linear.x != 0:

if self.msg.angular.z < self.speed:

self.msg.angular.z += 0.05

else:

self.msg.angular.z = self.speed*2

elif msg.data.find("右转") > -1:

if self.msg.linear.x != 0:

if self.msg.angular.z > -self.speed:

self.msg.angular.z -= 0.05

else:

self.msg.angular.z = -self.speed*2

elif msg.data.find("后退") > -1:

self.msg.linear.x = -self.speed

self.msg.angular.z = 0

elif msg.data.find("停止") > -1 or msg.data.find("立定") > -1:

self.msg = Twist()

self.pub_.publish(self.msg)

def cleanup(self):

# stop the robot!

twist = Twist()

self.pub_.publish(twist)

if __name__=="__main__":

rospy.init_node('voice_cmd_vel')

try:

voice_cmd_vel()

except:

pass