第八章 机器人语音交互 课后作业

代码包

所有代码已上传至github网站：
github链接: https://github.com/YuemingBi/ros_practice/tree/master

课后作业

第一题

1、ROS编译科大讯飞SDK

法一

ROS如何编译科大讯飞语音识别功能包，以前的文章里有写过https://blog.csdn.net/weixin_42361804/article/details/104145238。如果使用这种方式编译，只实现了科大讯飞的语音功能，本章作业的其他接口还要自行补充。

法二

下载科大讯飞SDK和我提供的ch8功能包，然后把SDK的libmsc.so拷贝到/usr/lib文件夹下，把ch8功能包的所有PPID改成自己的PPID（使用查找和替换），之后就可以编译使用了。

2、本章作业功能包解析

本章作业需要ch6和ch8功能包一起编译，其中ch8的launch文件和cpp文件如下图所示：

（1）voice_teleop.launch

<launch>

	<node name="iat_publish" pkg="robot_voice" type="iat_publish" output="screen"/>
	<node name="voice_teleop" pkg="robot_voice" type="voice_teleop" output="screen"/>
	<node name="voice_assistant" pkg="robot_voice" type="voice_assistant" output="screen"/>

</launch>

此launch文件启动三个节点，其中iat_publish是语音输入和语音识别的节点，voice_teleop是根据语音识别的结果控制机器人执行某种动作的节点，voice_assistant是根据语音识别的结果给出回应并语音输出的节点。

（2）iat_publish.cpp的main函数

int main(int argc, char* argv[])
{
	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);
	// 发布语音识别结果
	ros::Publisher voiceWordsPub = n.advertise<std_msgs::String>("voiceWords", 1000);

	ROS_INFO("Sleeping...");
	int count=0;
	
	int ret = MSP_SUCCESS;
	int upload_on =	1; /* whether upload the user word */
	/* login params, please do keep the appid correct */
	const char* login_params = "appid = 5d3ff09c, work_dir = .";
	int aud_src = 0; /* from mic or file */
	
	/*
	* See "iFlytek MSC Reference Manual"
	*/

	const char* session_begin_params =
		"sub = iat, domain = iat, language = zh_cn, "
		"accent = mandarin, sample_rate = 16000, "
		"result_type = plain, result_encoding = utf8";

	/* Login first. the 1st arg is username, the 2nd arg is password
	 * just set them as NULL. the 3rd arg is login paramertes
	 * */
	ret = MSPLogin(NULL, NULL, login_params);
	if (MSP_SUCCESS != ret)	{
		printf("MSPLogin failed , Error code %d.\n",ret);
		goto exit; // login fail, exit the program
	}

	while(ros::ok())
	{
			// 语音识别唤醒
			if(wakeupFlag)
			{

				ROS_INFO("Wakeup...");
				
				printf("Demo recognizing the speech from microphone\n");
				printf("Speak in 8 seconds\n");
				
				demo_mic(session_begin_params);
				
				printf("8 sec passed\n");
				wakeupFlag=0;
			}
			// 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;
}

此节点订阅了语音唤醒的话题/voiceWakeup，当接收到此话题的信号之后开始语音识别，然后将语音识别的结果发布给/voiceWords

（3）voice_teleop.cpp

#include "ros/ros.h"
#include "geometry_msgs/Twist.h"
#include "std_msgs/String.h"

class SubscribeAndPublish
{
public:
  SubscribeAndPublish()
  {
    pub = n.advertise<geometry_msgs::Twist>("cmd_vel", 1000);
    sub = n.subscribe("voiceWords", 1000, &SubscribeAndPublish::callback, this);
  }

  void callback(const std_msgs::String::ConstPtr& msg)
  {
      std::string dataString = msg->data;
      if(dataString.find("前进") != std::string::npos || dataString.find("向前") != std::string::npos){
            //ROS_INFO("go forward");
            geometry_msgs::Twist msg;
            msg.linear.x = 0.3;
            msg.angular.z = 0;
            pub.publish(msg);
      }
      else if(dataString.find("后退") != std::string::npos || dataString.find("向后") != std::string::npos){
            //ROS_INFO("go back");
            geometry_msgs::Twist msg;
            msg.linear.x = -0.3;
            msg.angular.z = 0;
            pub.publish(msg);
      }
      else if(dataString.find("左转") != std::string::npos || dataString.find("向左") != std::string::npos){
            //ROS_INFO("turn right");
            geometry_msgs::Twist msg;
            msg.linear.x = 0;
            msg.angular.z = 0.3;
            pub.publish(msg);
      }
      else if(dataString.find("右转") != std::string::npos || dataString.find("向左") != std::string::npos){
            //ROS_INFO("turn left");
            geometry_msgs::Twist msg;
            msg.linear.x = 0;
            msg.angular.z = -0.3;
            pub.publish(msg);
      }
      else if(dataString.find("转圈") != std::string::npos || dataString.find("转圈圈") != std::string::npos){
            geometry_msgs::Twist msg;
            msg.linear.x = 0.3;
            msg.angular.z = 0.3;
            pub.publish(msg);
      }
   }

private:
  ros::NodeHandle n;
  ros::Publisher pub;
  ros::Subscriber sub;

};

int main(int argc, char **argv)
{
  ros::init(argc, argv, "voice_teleop");
  SubscribeAndPublish SAPObject;
  ros::spin();

  return 0;
}

此节点订阅了/voiceWords话题，即语音识别的结果，然后根据语音识别的结果向/cmd_vel话题发布控制机器人速度的消息。

（3）voice_assistant.cpp

#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <unistd.h>

#include "robot_voice/qtts.h"
#include "robot_voice/msp_cmn.h"
#include "robot_voice/msp_errors.h"
#include "ros/ros.h"
#include "std_msgs/String.h"

/* wav音频头部格式 */
typedef struct _wave_pcm_hdr
{
	char            riff[4];                // = "RIFF"
	int		size_8;                 // = FileSize - 8
	char            wave[4];                // = "WAVE"
	char            fmt[4];                 // = "fmt "
	int		fmt_size;		// = 下一个结构体的大小 : 16
	short int       format_tag;             // = PCM : 1
	short int       channels;               // = 通道数 : 1
	int		samples_per_sec;        // = 采样率 : 8000 | 6000 | 11025 | 16000
	int		avg_bytes_per_sec;      // = 每秒字节数 : samples_per_sec * bits_per_sample / 8
	short int       block_align;            // = 每采样点字节数 : wBitsPerSample / 8
	short int       bits_per_sample;        // = 量化比特数: 8 | 16
	char            data[4];                // = "data";
	int		data_size;              // = 纯数据长度 : FileSize - 44
} wave_pcm_hdr;

/* 默认wav音频头部数据 */
wave_pcm_hdr default_wav_hdr =
{
	{ 'R', 'I', 'F', 'F' },
	0,
	{'W', 'A', 'V', 'E'},
	{'f', 'm', 't', ' '},
	16,
	1,
	1,
	16000,
	32000,
	2,
	16,
	{'d', 'a', 't', 'a'},
	0
};

/* 文本合成 */
int text_to_speech(const char* src_text, const char* des_path, const char* params)
{
	int          ret          = -1;
	FILE*        fp           = NULL;
	const char*  sessionID    = NULL;
	unsigned int audio_len    = 0;
	wave_pcm_hdr wav_hdr      = default_wav_hdr;
	int          synth_status = MSP_TTS_FLAG_STILL_HAVE_DATA;
	if (NULL == src_text || NULL == des_path)
	{
		printf("params is error!\n");
		return ret;
	}
	fp = fopen(des_path, "wb");
	if (NULL == fp)
	{
		printf("open %s error.\n", des_path);
		return ret;
	}
	
	/* 开始合成 */
	sessionID = QTTSSessionBegin(params, &ret);
	if (MSP_SUCCESS != ret)
	{
		printf("QTTSSessionBegin failed, error code: %d.\n", ret);
		fclose(fp);
		return ret;
	}
	ret = QTTSTextPut(sessionID, src_text, (unsigned int)strlen(src_text), NULL);

	if (MSP_SUCCESS != ret)
	{
		printf("QTTSTextPut failed, error code: %d.\n",ret);
		QTTSSessionEnd(sessionID, "TextPutError");
		fclose(fp);
		return ret;
	}

	printf("正在合成 ...\n");
	fwrite(&wav_hdr, sizeof(wav_hdr) ,1, fp); //添加wav音频头，使用采样率为16000
	while (1)
	{
		/* 获取合成音频 */
		const void* data = QTTSAudioGet(sessionID, &audio_len, &synth_status, &ret);
		if (MSP_SUCCESS != ret)
			break;
		if (NULL != data)
		{
			fwrite(data, audio_len, 1, fp);
		    wav_hdr.data_size += audio_len; //计算data_size大小
		}
		if (MSP_TTS_FLAG_DATA_END == synth_status)
			break;
		printf(">");
		usleep(150*1000); //防止频繁占用CPU
	}
	printf("\n");
	if (MSP_SUCCESS != ret)
	{
		printf("QTTSAudioGet failed, error code: %d.\n",ret);
		QTTSSessionEnd(sessionID, "AudioGetError");
		fclose(fp);
		return ret;
	}

	/* 修正wav文件头数据的大小 */
	wav_hdr.size_8 += wav_hdr.data_size + (sizeof(wav_hdr) - 8);
	
	/* 将修正过的数据写回文件头部,音频文件为wav格式 */
	fseek(fp, 4, 0);
	fwrite(&wav_hdr.size_8,sizeof(wav_hdr.size_8), 1, fp); //写入size_8的值
	fseek(fp, 40, 0); //将文件指针偏移到存储data_size值的位置
	fwrite(&wav_hdr.data_size,sizeof(wav_hdr.data_size), 1, fp); //写入data_size的值
	fclose(fp);
	fp = NULL;
	
	/* 合成完毕 */
	ret = QTTSSessionEnd(sessionID, "Normal");

	if (MSP_SUCCESS != ret)
	{
		printf("QTTSSessionEnd failed, error code: %d.\n",ret);
	}
	return ret;
}

std::string to_string(int val)

{
    char buf[20];
    sprintf(buf, "%d", val);
    return std::string(buf);
}

void voiceWordsCallback(const std_msgs::String::ConstPtr& msg)
{
    char cmd[2000];
    const char* text;
    int         ret                  = MSP_SUCCESS;
    const char* session_begin_params = "voice_name = xiaoyan, text_encoding = utf8, sample_rate = 16000, speed = 50, volume = 50, pitch = 50, rdn = 2";
    const char* filename             = "tts_sample.wav"; //合成的语音文件名称
    std::cout<<"I heard :"<<msg->data.c_str()<<std::endl;
	std::string dataString = msg->data;
	
	if(dataString.find("前进") != std::string::npos
    || dataString.find("向前") != std::string::npos)
    {
        char helpString[100] = "太阳当空照，花儿对我笑";
        text = helpString;
        std::cout<<text<<std::endl;
    }
    else if(dataString.find("后退") != std::string::npos
         || dataString.find("向后") != std::string::npos)
    {
        char helpString[100] = "后退，回首美丽的风景";
        text = helpString;
        std::cout<<text<<std::endl;
    }

    else if(dataString.find("左转") != std::string::npos
         || dataString.find("向左") != std::string::npos)
    {
        char helpString[100] = "峰回路转，向左转";
        text = helpString;
        std::cout<<text<<std::endl;
    }
    else if(dataString.find("右转") != std::string::npos
				|| dataString.find("向左") != std::string::npos)
    {
        char helpString[100] = "峰回路转，向右转";
        text = helpString;
        std::cout<<text<<std::endl;
    }
	else if(dataString.find("转圈") != std::string::npos
				|| dataString.find("转圈圈") != std::string::npos)
    {
        char helpString[100] = "爱的魔力转圈圈";
        text = helpString;
        std::cout<<text<<std::endl;
    }
    else
    {
        text = msg->data.c_str();
    }
    
    /* 文本合成 */
    printf("开始合成 ...\n");

    ret = text_to_speech(text, filename, session_begin_params);

    if (MSP_SUCCESS != ret)
    {
        printf("text_to_speech failed, error code: %d.\n", ret);
    }
    printf("合成完毕\n");
    popen("play tts_sample.wav","r");
    sleep(1);
}

void toExit()
{
    printf("按任意键退出 ...\n");
    getchar();
    MSPLogout(); //退出登录
}

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

{

	int         ret                  = MSP_SUCCESS;

	const char* login_params         = "appid = 5d3ff09c, work_dir = .";//登录参数,appid与msc库绑定,请勿随意改动

	/* 用户登录 */
	ret = MSPLogin(NULL, NULL, login_params);//第一个参数是用户名，第二个参数是密码，第三个参数是登录参数，用户名和密码可在http://www.xfyun.cn注册获取
	if (MSP_SUCCESS != ret)
	{
		printf("MSPLogin failed, error code: %d.\n", ret);
		//goto exit ;//登录失败，退出登录
		toExit();
	}

	ros::init(argc,argv,"TextToSpeech");
	ros::NodeHandle n;
	ros::Subscriber sub =n.subscribe("voiceWords", 1000, voiceWordsCallback);
	ros::spin();

exit:
	printf("按任意键退出 ...\n");
	getchar();
	MSPLogout(); //退出登录
	
	return 0;
}

此节点订阅了语音合成结果的话题/voiceWords，然后根据语音识别结果作出回应并语音合成。从回调函数voiceWordsCallback()中可以看到前进、后退、左转、右转、转圈的五种情况。

3、运行结果

（1）运行仿真环境和语音控制节点

roslaunch robot_voice voice_teleop.launch
roslaunch robot_gazebo view_robot_kinect_rplidar.launch

（2）太阳当空照，花儿对我笑

rostopic pub /voiceWakeup std_msgs/String "data: ''"
语音输入“前进”或“向前”，机器人向前运动，并回答“太阳当空照，花儿对我笑”

（3）后退，回首美丽的风景

rostopic pub /voiceWakeup std_msgs/String "data: ''"
语音输入“后退”或“向后”，机器人向后运动，并回答“后退，回首美丽的风景”

（4）峰回路转，向左转

rostopic pub /voiceWakeup std_msgs/String "data: ''"
语音输入“左转”或“向左”，机器人向左转，并回答“峰回路转，向左转”

（5）峰回路转，向右转

rostopic pub /voiceWakeup std_msgs/String "data: ''"
语音输入“右转”或“向右”，机器人向右转，并回答“峰回路转，向右转”

（6）爱的魔力转圈圈

rostopic pub /voiceWakeup std_msgs/String "data: ''"
语音输入“转圈”，机器人转圈，并回答“爱的魔力转圈圈”