目录

一、总体介绍

二、环境设置与安装

三、语音识别

四、语音合成

五、GPT调用

六、信息关系

 七、实现效果

---

一、总体介绍

达成效果：在ROS系统中实现用户语音提问得到智能语音回答

用到的技术：科大讯飞的语音识别、语音合成

                      GPT

操作系统：ubuntu20.04

二、环境设置与安装

（1）安装ROS

用鱼香ROS一键安装

wget http://fishros.com/install -O fishros && . fishros

（2）安装依赖包

使用python调用ChatGPT的API，依赖于python中的openai库，安装openai库的命令

pip install openai

三、语音识别

#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <unistd.h>
#include <termio.h>
#include "qisr.h"
#include "msp_cmn.h"
#include "msp_errors.h"
#include "speech_recognizer.h"
#include <iconv.h>

#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");
    printf("Press \"Space\" key Stop\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++ < 10)
    //     sleep(1);
    int ch;
    while(1){
        ch = getchar();
        if(ch == 32){
            printf("\nSpeaking done \n");
            break;
        }
            
    }
    errcode = sr_stop_listening(&iat);
    if (errcode) {
        printf("stop listening failed %d\n", errcode);
    }

    sr_uninit(&iat);
}


int main(int argc, char* argv[])
{
    ros::init(argc, argv, "iFlyAutoTransform");
    ros::NodeHandle n;
    ros::Rate loop_rate(10);  
    ros::Publisher iat_text_pub = n.advertise<std_msgs::String>("iat_text", 1000);  

    termios tms_old, tms_new;
    tcgetattr(0, &tms_old); 
    tms_new = tms_old;
    tms_new.c_lflag &= ~(ICANON | ECHO);
    tcsetattr(0, TCSANOW, &tms_new);

    ROS_INFO("Press \"Space\" key to Start,Press \"Enter\" key to Exit.");
    int count=0;
    int ch;
    while(ros::ok())
    {
        ch = getchar();
        printf("Pressed Key Value %d\n",ch);
        if(ch == 32){  //Space key
            wakeupFlag = 1;
        }
        if(ch == 10){  //Enter key
            ROS_INFO("Node Exit.");
            break;
        }
        if (wakeupFlag){
            int ret = MSP_SUCCESS;
            /* login params, please do keep the appid correct */
            const char* login_params = "appid = 你的id, work_dir = ."; //appid need match with you SDK file

            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 10 seconds\n");
            demo_mic(session_begin_params);
            // printf("10 sec passed\n");
            wakeupFlag=0;
            MSPLogout();
        }
        // 语音识别完成
        if(resultFlag){
            resultFlag=0;
            std_msgs::String msg;
            msg.data = g_result;
            iat_text_pub.publish(msg);
        }
        ROS_INFO("Press \"Space\" key to Start,Press \"Enter\" key to Exit.");
        ros::spinOnce();
        loop_rate.sleep();
        count++;
    }

exit:
    tcsetattr(0, TCSANOW, &tms_old);
    MSPLogout(); // Logout...
    return 0;
}

四、语音合成

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


#include "qtts.h"
#include "msp_cmn.h"
#include "msp_errors.h"

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

#include <sstream>
#include <sys/types.h>
#include <sys/stat.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
    }//合成状态synth_status取值请参阅《讯飞语音云API文档》
    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;
}

void ttsCallback(const std_msgs::String::ConstPtr& msg)
{
    char cmd[2000];
    const char* text;
    int         ret                  = MSP_SUCCESS;
    const char* session_begin_params = "voice_name = x4_twcn_ziwen_assist, 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;
    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");


    unlink("/tmp/cmd");  
    mkfifo("/tmp/cmd", 0777);  
    popen("mplayer -quiet -slave -input file=/tmp/cmd 'tts_sample.wav'","r");
    sleep(3);
}

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 = 你的id, work_dir = ."; //appid need match with you SDK file
    /*
    * rdn:           合成音频数字发音方式
    * volume:        合成音频的音量
    * pitch:         合成音频的音调
    * speed:         合成音频对应的语速
    * voice_name:    合成发音人
    * sample_rate:   合成音频采样率
    * text_encoding: 合成文本编码格式
    *
    * 详细参数说明请参阅《讯飞语音云MSC--API文档》
    */

    /* 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://open.voicecloud.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 tts_text_pub =n.subscribe("gpt_reply_to_user", 1000,ttsCallback);
    ros::spin();

exit:
    MSPLogout(); //退出登录
    return 0;
}

五、GPT调用

#!/usr/bin/env python3
import rospy
from std_msgs.msg import String
from openai import OpenAI

# 初始化OpenAI客户端
client = OpenAI(
    api_key="your api key here!!"
)

def user_message_callback(data):
    rospy.loginfo("Received from user: %s", data.data)

    # 向GPT发送请求，并获取回复
    chat_completion = client.chat.completions.create(
    messages = [
        {
            "role":"user",
         "content":data.data
         },    
    ],
    model="gpt-3.5-turbo"
    )
    # 获取GPT的回复
    gpt_reply = chat_completion.choices[0].message.content
    rospy.loginfo("GPT Reply: %s", gpt_reply)

    # 发布GPT的回复
    gpt_reply_pub.publish(gpt_reply)

if __name__ == '__main__':
    try:
        rospy.init_node('chatgpt_ros_node', anonymous=True)

        # 订阅用户消息
        rospy.Subscriber("iat_text", String, user_message_callback)

        # 创建发布者，用于发布GPT的回复
        gpt_reply_pub = rospy.Publisher("gpt_reply_to_user", String, queue_size=10)

        rospy.spin()
    except rospy.ROSInterruptException:
        pass

六、信息关系

 七、实现效果

运行步骤

第一个终端

roscore

第二个终端

rosrun robot_voice chatgpt_communication.py 

 第三个终端

rosrun robot_voice tts_subscribe

第四个终端

rosrun robot_voice iat_publish

 在第四个终端根据提示提问就行了