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
//#include
using 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<<"收到："<data.c_str()<data.c_str();
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<<"11111"<("/cmd_vel_mux/input/teleop",10);
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<<"您好！你可以语音控制啦！"<前进"<后退"<左转"<右转"<停止"< 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