ROS中阶笔记(六):机器人感知—机器语音
1 语音识别理论
2 常用语音功能包
- pocketsphinx:集成CMU Sphinx和Festival开源项目中的代码,实现语音识别的功能
- audio-common:提供了文本转语音的功能实现完成"机器人说话"的想法
- AIML:人工智能标记语音,Artificial Intelligence Markup Language是一种创建自然语音软件代理的XML语言
3 科大讯飞SDK
登录科大讯飞开放平台的官方网站:http://www.xfyun.cn/,注册一个账户并下载SDK
下载的SDK文件(Linux_lat···文件)——解压——示例在samples文件夹下面(比如iat_record_sample,刚下载完成功能包之后,需要咋当前目录下面编译,通过make编译)
编译之后的文件放在bin文件夹下面的,可以看到有一个生成的可执行文件iat_record_sample;
3.1 使用前提
将科大讯飞SDK的库文件拷贝到系统目录下
$ sudo cp libmsc.so/usr/lib/libmsc.so # (注意选择相应的处理器架构)
# SDK的库文件在libs中有(x86和x64,在这里面放置的库文件)
科大讯飞的SDK带有ID号,每个人每次下载后的ID都不相同,更换SDK之后需要修改代码中的APPID,你也可以直接使用本课程的libmsc.so文件,否则需要将源码中的APPID修改为自己下载SDK中的ID。
3.2 语音听写
iat_publish.cpp
/*
* 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 <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <unistd.h>
#include "robot_voice/qisr.h"
#include "robot_voice/msp_cmn.h"
#include "robot_voice/msp_errors.h"
#include "robot_voice/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("
Result: [ %s ]", string);
if(is_over)
putchar('
');
}
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
");
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...
");
}
void on_speech_end(int reason)
{
if (reason == END_REASON_VAD_DETECT)
printf("
Speaking done
");
else
printf("
Recognizer error %d
", 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
");
return;
}
errcode = sr_start_listening(&iat);
if (errcode) {
printf("start listen failed %d
", errcode);
}
/* demo 10 seconds recording */
while(i++ < 10)
sleep(1);
errcode = sr_stop_listening(&iat);
if (errcode) {
printf("stop listening failed %d
", 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
");
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<std_msgs::String>("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 = 594a7b46, 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.
",ret);
}
printf("Demo recognizing the speech from microphone
");
printf("Speak in 10 seconds
");
demo_mic(session_begin_params);
printf("10 sec passed
");
wakeupFlag=0;
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;
}
subscriber(订阅者):用来接收语音唤醒信号,接收到唤醒信号之后,会将wakeupFlag变量置位;
主循环中调用SDK的语音听写功能,识别成功后置位resultFlag变量,通过Publisher将识别出来的字符串发布。
第一步,在CMakeLists.txt中加入编译规则
add_executable(iat_publish
src/iat_publish.cpp
src/speech_recognizer.c
src/linuxrec.c)
target_link_libraries(
iat_publish
${catkin_LIBRARIES}
libmsc.so -ldl -lpthread -lm -lrt -lasound
)
编译过程需要链接SDK中的libmsc.so库,此前已经将此库拷贝到系统路径下,所以此处不需要添加完整路径。
第二步,语音听写示例
$ roscore
$ rosrun robot_voice iat_publish
$ rostopic pub /voiceWakeup std_msgs/String "data:'any string'"
'any string' ''里面可以随便填
3.3 语音合成
语音合成(Text To Speech,TTS)技术能够自动将任意文字实时转换为连续的自然语音,是一种能够在任何时间、任何地点,向任何人提供语音信息服务的高效便捷手段,非常符合信息时代海量数据、动态更新和个性化查询的需求。
tts_subscribe.cpp
/*
* 语音合成(Text To Speech,TTS)技术能够自动将任意文字实时转换为连续的
* 自然语音,是一种能够在任何时间、任何地点,向任何人提供语音信息服务的
* 高效便捷手段,非常符合信息时代海量数据、动态更新和个性化查询的需求。
*/
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <unistd.h>
#include <errno.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"
#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!
");
return ret;
}
fp = fopen(des_path, "wb");
if (NULL == fp)
{
printf("open %s error.
", des_path);
return ret;
}
/* 开始合成 */
sessionID = QTTSSessionBegin(params, &ret);
if (MSP_SUCCESS != ret)
{
printf("QTTSSessionBegin failed, error code: %d.
", 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.
",ret);
QTTSSessionEnd(sessionID, "TextPutError");
fclose(fp);
return ret;
}
printf("正在合成 ...
");
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("
");
if (MSP_SUCCESS != ret)
{
printf("QTTSAudioGet failed, error code: %d.
",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.
",ret);
}
return ret;
}
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;
text = msg->data.c_str();
/* 文本合成 */
printf("开始合成 ...
");
ret = text_to_speech(text, filename, session_begin_params);
if (MSP_SUCCESS != ret)
{
printf("text_to_speech failed, error code: %d.
", ret);
}
printf("合成完毕
");
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 ...
");
getchar();
MSPLogout(); //退出登录
}
int main(int argc, char* argv[])
{
int ret = MSP_SUCCESS;
const char* login_params = "appid = 594a7b46, work_dir = .";//登录参数,appid与msc库绑定,请勿随意改动
/*
* 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.
", ret);
/*goto exit ;*///登录失败,退出登录
toExit();
}
printf("
###########################################################################
");
printf("## 语音合成(Text To Speech,TTS)技术能够自动将任意文字实时转换为连续的 ##
");
printf("## 自然语音,是一种能够在任何时间、任何地点,向任何人提供语音信息服务的 ##
");
printf("## 高效便捷手段,非常符合信息时代海量数据、动态更新和个性化查询的需求。 ##
");
printf("###########################################################################
");
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 ...
");
getchar();
MSPLogout(); //退出登录
return 0;
}
- main函数中声明了一个订阅voiceWords话题的subscriber,接收输入的语音字符串。
- 回调函数voiceWordsCallback中使用SDK接口将字符串转换成中文语音。
第一步,在CMakeLists.txt中加入编译规则
add_executable(tts_subscribe src/tts_subscribe.cpp)
target_link_libraries(
tts_subscribe
${catkin_LIBRARIES}
libmsc.so -ldl -pthread
)
第二步,语音合成示例
$ roscore
$ rosrun robot_voice tts_subscribe
$ rostopic pub/voiceWords std_msgs/String"data:'你好,我是机器人'"
语音合成启动后可能产生的错误
原因:mplayer配置导致
解决方法:在$HOME/.mplayer/config文件中添加如下设置:lirc=no
3.4 智能语音助手
voice_assistant.cpp
#include <iostream>
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <unistd.h>
#include <errno.h>
#include <time.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"
#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!
");
return ret;
}
fp = fopen(des_path, "wb");
if (NULL == fp)
{
printf("open %s error.
", des_path);
return ret;
}
/* 开始合成 */
sessionID = QTTSSessionBegin(params, &ret);
if (MSP_SUCCESS != ret)
{
printf("QTTSSessionBegin failed, error code: %d.
", 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.
",ret);
QTTSSessionEnd(sessionID, "TextPutError");
fclose(fp);
return ret;
}
printf("正在合成 ...
");
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("
");
if (MSP_SUCCESS != ret)
{
printf("QTTSAudioGet failed, error code: %d.
",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.
",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.compare("你是谁?") == 0)
{
char nameString[40] = "我是你的语音小助手";
text = nameString;
std::cout<<text<<std::endl;
}
else if(dataString.compare("你可以做什么?") == 0)
{
char helpString[40] = "你可以问我现在时间";
text = helpString;
std::cout<<text<<std::endl;
}
else if(dataString.compare("现在时间。") == 0)
{
//获取当前时间
struct tm *ptm;
long ts;
ts = time(NULL);
ptm = localtime(&ts);
std::string string = "现在时间" + to_string(ptm-> tm_hour) + "点" + to_string(ptm-> tm_min) + "分";
char timeString[40];
string.copy(timeString, sizeof(string), 0);
text = timeString;
std::cout<<text<<std::endl;
}
else
{
text = msg->data.c_str();
}
/* 文本合成 */
printf("开始合成 ...
");
ret = text_to_speech(text, filename, session_begin_params);
if (MSP_SUCCESS != ret)
{
printf("text_to_speech failed, error code: %d.
", ret);
}
printf("合成完毕
");
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 ...
");
getchar();
MSPLogout(); //退出登录
}
int main(int argc, char* argv[])
{
int ret = MSP_SUCCESS;
const char* login_params = "appid = 594a7b46, work_dir = .";//登录参数,appid与msc库绑定,请勿随意改动
/*
* 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.
", ret);
/*goto exit ;*///登录失败,退出登录
toExit();
}
printf("
###########################################################################
");
printf("## 语音合成(Text To Speech,TTS)技术能够自动将任意文字实时转换为连续的 ##
");
printf("## 自然语音,是一种能够在任何时间、任何地点,向任何人提供语音信息服务的 ##
");
printf("## 高效便捷手段,非常符合信息时代海量数据、动态更新和个性化查询的需求。 ##
");
printf("###########################################################################
");
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 ...
");
getchar();
MSPLogout(); //退出登录
return 0;
}
第一步,在CMakeLists.txt中加入编译规则
add_executable(voice_assistant src/voice_assistant.cpp)
target_link_libraries(
voice_assistant
${catkin_LIBRARIES}
libmsc.so -ldl -pthread
)
第二步,智能语音助手示例
$ roscore
$ rosrun robot_voice iat_publish # 启动语音识别节点
$ rosrun robot_voice voice_assistant # 启动语音助手作为语音判断
$ rostopic pub /voiceWakeup std_msgs/String "data:'any string'" # 唤醒词
4 参考资料
1.ROS探索总结(二十八)——机器听觉
2.ROS Kinetic使用PocketSphinx进行语音识别
https://blog.csdn.net/seeseeatre/article/details/79228816
3.讯飞开放平台-以语音交互为核心的人工智能开放平台
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