讯飞离线语音命令词+TTS离线发音，实现命令词交互（windows dll for unity插件）
2024-06-07 04:53:22
步骤一
登录讯飞平台注册并创建自己的应用
https://www.xfyun.cn
步骤二
下载离线命令词识别SDK windows MSC ，注意下载的SDK会根据你的appid捆绑在代码段里，应该是讯飞的版权策略
步骤三
下载离线语音合成（普通版）SDK ，
步骤四
根据官方提示需要使用 vs2010 版本 不想折腾版本兼容问题，就乖乖安装。
链接：网盘下载地址 提取码：9541
步骤五
1.解压 离线命令词识别SDK压缩包 和 离线语音合成（普通版）压缩包。
2.使用vs2010打开项目/解决方案 打开解压后samples文件夹里的工程文件。
3.配置换开发环境 ，请参考 离线命令词识别 Windows SDK 文档 和 离线语音合成 Windows SDK 文档
4.确定samples工程可以正常运行。
步骤六
将离线语音合成打包成DLL库
1.当前运行的工程为win32控制台模式，修改成dll ，右键项目解决方案 -> 属性 ->常规->配置类型修改成（动态库.dll）
2.替换下面改造dll代码，tts_offline_sample.c，注意替换成自己的appid
/*
* 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 <stdlib.h>
#include <stdio.h>
#include <errno.h>
#include <intrin.h>#include <string.h>
#include <Windows.h>
#include <locale.h>#include "qtts.h"
#include "msp_cmn.h"
#include "msp_errors.h"#ifdef _WIN64
#pragma comment(lib,"../../libs/msc_x64.lib")//x64
#else
#pragma comment(lib,"../../libs/msc.lib")//x86
#endif/* wav音频头部格式 */
typedef struct _wave_pcm_hdr
{char riff[4]; // = "RIFF"int size_8; // = FileSize - 8char wave[4]; // = "WAVE"char fmt[4]; // = "fmt "int fmt_size; // = 下一个结构体的大小 : 16short int format_tag; // = PCM : 1short int channels; // = 通道数 : 1int samples_per_sec; // = 采样率 : 8000 | 6000 | 11025 | 16000int avg_bytes_per_sec; // = 每秒字节数 : samples_per_sec * bits_per_sample / 8short int block_align; // = 每采样点字节数 : wBitsPerSample / 8short int bits_per_sample; // = 量化比特数: 8 | 16char 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
};char *wchar_t_to_char(const wchar_t *str){char *result = NULL;int textlen = 0;textlen = WideCharToMultiByte(CP_ACP,0,str,-1,NULL,0,NULL,NULL);result = (char*)malloc((textlen+1)*sizeof(char));memset(result,0,sizeof(char)*(textlen+1));WideCharToMultiByte(CP_ACP,0,str,-1,result,textlen,NULL,NULL);return result;
}/* 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 0;}fp = fopen(des_path, "wb");if (NULL == fp){printf("open %s error.\n", des_path);return 1;}/* 开始合成 */sessionID = QTTSSessionBegin(params, &ret);if (MSP_SUCCESS != ret){printf("QTTSSessionBegin failed, error code: %d.\n", ret);fclose(fp);return 2;}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 3;}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16000while (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("\n");if (MSP_SUCCESS != ret){printf("QTTSAudioGet failed, error code: %d.\n",ret);QTTSSessionEnd(sessionID, "AudioGetError");fclose(fp);return 4;}/* 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 5;
}/* 用户登录 */
__declspec(dllexport) int loading_tts(){int ret = MSP_SUCCESS;const char* login_params = "appid = 替换自己的appid, work_dir = .";//登录参数,appid与msc库绑定,请勿随意改动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){MSPLogout(); return 0;}return 1;
}/* 开始转换 */
__declspec(dllexport) int to_speech(wchar_t * wav_path, wchar_t * tts_text){int ret = MSP_SUCCESS;const char* session_begin_params = "engine_type = local, voice_name = xiaoyan, text_encoding = GB2312, tts_res_path = fo|C:\\xunfei_speech\\xiaoyan.jet;fo|C:\\xunfei_speech\\common.jet, sample_rate = 16000, speed = 50, volume = 50, pitch = 50, rdn = 2";//const char* filename = "C:\\xunfei_speech\\tts_sample.wav"; //合成的语音文件名称s//const char* text = "亲爱的用户，您好，这是一个语音合成示例，感谢您对小螺丝语音技术的支持！小螺丝是亚太地区最大的上市公司，股票代码：002233"; //合成文本const char* filename =wchar_t_to_char(wav_path);const char* text =wchar_t_to_char(tts_text);ret = text_to_speech(text, filename, session_begin_params);return ret;
}/* 释放 */
__declspec(dllexport) int free_tts(){MSPLogout(); return 1;
}3.重新生成DLL
步骤七
将离线语音命令词打包成DLL库
1.当前运行的工程为win32控制台模式，修改成dll ，右键项目解决方案 -> 属性 ->常规->配置类型修改成（动态库.dll）
2.替换下面改造dll代码，asr_record_sample.c，注意替换成自己的appid
/*
* 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 <windows.h>
#include <conio.h>
#include <errno.h>
#include <process.h>#include "../../include/qisr.h"
#include "../../include/msp_cmn.h"
#include "../../include/msp_errors.h"
#include "./include/speech_recognizer.h"#define FRAME_LEN 640
#define BUFFER_SIZE 4096enum{EVT_START = 0,EVT_STOP,EVT_QUIT,EVT_TOTAL
};
static HANDLE events[EVT_TOTAL] = {NULL,NULL,NULL};static COORD begin_pos = {0, 0};
static COORD last_pos = {0, 0};
#define SAMPLE_RATE_16K (16000)
#define SAMPLE_RATE_8K (8000)
#define MAX_GRAMMARID_LEN (32)
#define MAX_PARAMS_LEN (1024)const char * ASR_RES_PATH = "fo|C:\\xunfei_speech\\command_speech\\common.jet"; //离线语法识别资源路径
#ifdef _WIN64
const char * GRM_BUILD_PATH = "C:\\xunfei_speech\\command_speech\\GrmBuilld_x64"; //构建离线语法识别网络生成数据保存路径
#else
const char * GRM_BUILD_PATH = "C:\\xunfei_speech\\command_speech\\GrmBuilld"; //构建离线语法识别网络生成数据保存路径
#endif
const char * GRM_FILE = "C:\\xunfei_speech\\command_speech\\call.bnf"; //构建离线识别语法网络所用的语法文件
const char * LEX_NAME = "contact"; //更新离线识别语法的contact槽（语法文件为此示例中使用的call.bnf）
typedef struct _UserData {int build_fini; //标识语法构建是否完成int update_fini; //标识更新词典是否完成int errcode; //记录语法构建或更新词典回调错误码char grammar_id[MAX_GRAMMARID_LEN]; //保存语法构建返回的语法ID
}UserData;const char *get_audio_file(void); //选择进行离线语法识别的语音文件
int build_grammar(UserData *udata); //构建离线识别语法网络
int update_lexicon(UserData *udata); //更新离线识别语法词典
int run_asr(UserData *udata); //进行离线语法识别int build_grm_cb(int ecode, const char *info, void *udata)
{UserData *grm_data = (UserData *)udata;if (NULL != grm_data) {grm_data->build_fini = 1;grm_data->errcode = ecode;}if (MSP_SUCCESS == ecode && NULL != info) {printf("构建语法成功！ 语法ID:%s\n", info);if (NULL != grm_data)_snprintf(grm_data->grammar_id, MAX_GRAMMARID_LEN - 1, info);}elseprintf("构建语法失败！%d\n", ecode);return 0;
}int build_grammar(UserData *udata)
{FILE *grm_file = NULL;char *grm_content = NULL;unsigned int grm_cnt_len = 0;char grm_build_params[MAX_PARAMS_LEN] = {NULL};int ret = 0;grm_file = fopen(GRM_FILE, "rb"); if(NULL == grm_file) {printf("打开\"%s\"文件失败！[%s]\n", GRM_FILE, strerror(errno));return -1; }fseek(grm_file, 0, SEEK_END);grm_cnt_len = ftell(grm_file);fseek(grm_file, 0, SEEK_SET);grm_content = (char *)malloc(grm_cnt_len + 1);if (NULL == grm_content){printf("内存分配失败!\n");fclose(grm_file);grm_file = NULL;return -1;}fread((void*)grm_content, 1, grm_cnt_len, grm_file);grm_content[grm_cnt_len] = '\0';fclose(grm_file);grm_file = NULL;_snprintf(grm_build_params, MAX_PARAMS_LEN - 1, "engine_type = local, \asr_res_path = %s, sample_rate = %d, \grm_build_path = %s, ",ASR_RES_PATH,SAMPLE_RATE_16K,GRM_BUILD_PATH);ret = QISRBuildGrammar("bnf", grm_content, grm_cnt_len, grm_build_params, build_grm_cb, udata);free(grm_content);grm_content = NULL;return ret;
}int update_lex_cb(int ecode, const char *info, void *udata)
{UserData *lex_data = (UserData *)udata;if (NULL != lex_data) {lex_data->update_fini = 1;lex_data->errcode = ecode;}if (MSP_SUCCESS == ecode)printf("更新词典成功！\n");elseprintf("更新词典失败！%d\n", ecode);return 0;
}int update_lexicon(UserData *udata)
{const char *lex_content = "丁伟\n黄辣椒";unsigned int lex_cnt_len = strlen(lex_content);char update_lex_params[MAX_PARAMS_LEN] = {NULL}; _snprintf(update_lex_params, MAX_PARAMS_LEN - 1, "engine_type = local, text_encoding = GB2312, \asr_res_path = %s, sample_rate = %d, \grm_build_path = %s, grammar_list = %s, ",ASR_RES_PATH,SAMPLE_RATE_16K,GRM_BUILD_PATH,udata->grammar_id);return QISRUpdateLexicon(LEX_NAME, lex_content, lex_cnt_len, update_lex_params, update_lex_cb, udata);
}static void show_result(char *string, char is_over)
{COORD orig, current;CONSOLE_SCREEN_BUFFER_INFO info;HANDLE w = GetStdHandle(STD_OUTPUT_HANDLE);GetConsoleScreenBufferInfo(w, &info);current = info.dwCursorPosition;if(current.X == last_pos.X && current.Y == last_pos.Y ) {SetConsoleCursorPosition(w, begin_pos);} else {/* changed by other routines, use the new pos as start */begin_pos = current;}if(is_over)SetConsoleTextAttribute(w, FOREGROUND_GREEN);printf("Result: [ %s ]\n", string);if(is_over)SetConsoleTextAttribute(w, info.wAttributes);GetConsoleScreenBufferInfo(w, &info);last_pos = info.dwCursorPosition;
}static char *g_result = NULL; //static char bk_result[1024]="0";static unsigned int g_buffersize = BUFFER_SIZE;
static UserData g_asr_data;
struct speech_rec g_asr;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);printf(g_result);strcpy(bk_result,g_result);//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");// g_result = (char*)"Speaking done";//strcpy(bk_result,"Speaking done");}else{printf("\nRecognizer error %d\n", reason);//g_result = (char*)"Recognizer error";//strcpy(bk_result,"Recognizer error");}
}/* demo recognize the audio from microphone */
static void recognize_mic(const char* session_begin_params)
{int errcode;int i = 0;HANDLE helper_thread = NULL;DWORD waitres;char isquit = 0;struct speech_rec_notifier recnotifier = {on_result,on_speech_begin,on_speech_end};errcode = sr_init(&g_asr, session_begin_params, SR_MIC, DEFAULT_INPUT_DEVID, &recnotifier);if (errcode) {printf("speech recognizer init failed\n");return;}
}int run_asr(UserData *udata)
{char asr_params[MAX_PARAMS_LEN] = {NULL};const char *rec_rslt = NULL;const char *session_id = NULL;const char *asr_audiof = NULL;FILE *f_pcm = NULL;char *pcm_data = NULL;long pcm_count = 0;long pcm_size = 0;int last_audio = 0;int aud_stat = MSP_AUDIO_SAMPLE_CONTINUE;int ep_status = MSP_EP_LOOKING_FOR_SPEECH;int rec_status = MSP_REC_STATUS_INCOMPLETE;int rss_status = MSP_REC_STATUS_INCOMPLETE;int errcode = -1;int aud_src = 1;//离线语法识别参数设置_snprintf(asr_params, MAX_PARAMS_LEN - 1, "engine_type = local, \asr_res_path = %s, sample_rate = %d, \grm_build_path = %s, local_grammar = %s, \result_type = xml, result_encoding = GB2312, ",ASR_RES_PATH,SAMPLE_RATE_16K,GRM_BUILD_PATH,udata->grammar_id);recognize_mic(asr_params);return 0;
}int main(int argc, char* argv[]){const char *login_config = "appid = 5fa0d519"; //登录参数int ret = 0 ;ret = MSPLogin(NULL, NULL, login_config); //第一个参数为用户名，第二个参数为密码，传NULL即可，第三个参数是登录参数if (MSP_SUCCESS != ret) {printf("登录失败：%d\n", ret);//goto exit;}memset(&g_asr_data, 0, sizeof(UserData));printf("构建离线识别语法网络...\n");ret = build_grammar(&g_asr_data); //第一次使用某语法进行识别，需要先构建语法网络，获取语法ID，之后使用此语法进行识别，无需再次构建if (MSP_SUCCESS != ret) {printf("构建语法调用失败！\n");}while (1 != g_asr_data.build_fini)_sleep(300);if (MSP_SUCCESS != g_asr_data.errcode)printf("离线识别语法网络构建完成，开始识别...\n"); ret = run_asr(&g_asr_data);if (MSP_SUCCESS != ret) {printf("离线语法识别出错: %d \n", ret);}while(1){sr_start_listening(&g_asr);_sleep(1000);}return 1;
}//初始化登录
__declspec(dllexport) int loading_msp(){const char *login_config = "appid = 替换自己的appid"; //登录参数int ret = 0 ;ret = MSPLogin(NULL, NULL, login_config); //第一个参数为用户名，第二个参数为密码，传NULL即可，第三个参数是登录参数if (MSP_SUCCESS != ret) {MSPLogout();return 0;}memset(&g_asr_data, 0, sizeof(UserData));return 1;
}/* 构建命令词网络 */
__declspec(dllexport) int build_net_msp(){int ret = 0 ;printf("构建离线识别语法网络...\n");ret = build_grammar(&g_asr_data); //第一次使用某语法进行识别，需要先构建语法网络，获取语法ID，之后使用此语法进行识别，无需再次构建if (MSP_SUCCESS != ret) {printf("构建语法调用失败！\n");return -1;}while (1 != g_asr_data.build_fini)_sleep(300);if (MSP_SUCCESS != g_asr_data.errcode)return 0;return 1;
}/* 更新词典槽 */
__declspec(dllexport) int update_lexicon_msp(){int ret = 0 ;printf("更新离线语法词典...\n");ret = update_lexicon(&g_asr_data); //当语法词典槽中的词条需要更新时，调用QISRUpdateLexicon接口完成更新if (MSP_SUCCESS != ret) {printf("更新词典调用失败！\n");return 0;}while (1 != g_asr_data.update_fini)_sleep(300);if (MSP_SUCCESS != g_asr_data.errcode)return 0;return 1;
}/* 识别命令词 */
__declspec(dllexport) int init_run_msp(){int ret = 0 ;ret = run_asr(&g_asr_data);if (MSP_SUCCESS != ret) {printf("离线语法识别出错: %d \n", ret);return 0;}return 1;
}static wchar_t * char2wchar(char *str){ int length = strlen(str)+1;wchar_t *t = (wchar_t*)malloc(sizeof(wchar_t)*length);memset(t,0,length*sizeof(wchar_t));MultiByteToWideChar(CP_ACP,0,str,strlen(str),t,length);return t;
}/* 识别命令词 */
__declspec(dllexport) wchar_t* start_listening(){wchar_t* re;if (sr_start_listening(&g_asr)!=NULL){// char * str1 = "小螺丝科技有限公司hahah1523";//g_result}re = char2wchar(bk_result); strcpy(bk_result,"0");return re;
}/* 释放 */
__declspec(dllexport) int free_msp(){MSPLogout();return 1;
}
3.编译，重新生成DLL
4.提示 ：打包dll后，确保在dll在unity里能够正常读取讯飞语音包引擎文件，这里添加了绝对路径 ，创建文件夹 c:\xunfei_speech 将SDK里的资源文件复制进去确保能够真确引用。
步骤八 Unity 调用 dll 实现业务交互调用
1.创建unity工程 speech_demo
2.Unity项目目录 Assets/Scenes 目录下创建目录 全路径为 Assets/Scenes/Plugins/Windows/X86_64（64位平台） Assets/Scenes/Plugins/Windows/X86（32位平台）创建Unity可引用的dll目录，将 asr_record_sample.dll、tts_offline_sample.dll，msc_x64.dll(两个引擎可共用一个)，x86平台为msc_x.dll，复制到目录下。
3.创建脚本ToSpeech.cs，脚本代码如下：
using System.Collections;
using System.Collections.Generic;
using UnityEngine;using System;
using System.Text;
using System.Linq;
using System.IO;
using System.Xml;using System.Runtime.InteropServices;public class ToSpeech : MonoBehaviour
{//初始化TTS离线朗读语音引擎[DllImport("tts_offline_sample", EntryPoint = "loading_tts", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]extern static int loading_tts();//合成语音文件[DllImport("tts_offline_sample", EntryPoint = "to_speech", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]extern static int to_speech([MarshalAs(UnmanagedType.LPWStr)]string wav_path, [MarshalAs(UnmanagedType.LPWStr)]string tts_text);//释放TTS朗读语音引擎[DllImport("tts_offline_sample", EntryPoint = "free_tts", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]extern static int free_tts();//初始化命令词识别离线引擎[DllImport("asr_offline_record_sample", EntryPoint = "loading_msp", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]public static extern int loading_msp();//初始化预热识别[DllImport("asr_offline_record_sample", EntryPoint = "init_run_msp", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]static extern int init_run_msp(); //构建识别网络[DllImport("asr_offline_record_sample", EntryPoint = "build_net_msp", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]static extern int build_net_msp();//更新词典槽[DllImport("asr_offline_record_sample", EntryPoint = "update_lexicon_msp", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]static extern int update_lexicon_msp();//开启监听——micphone[DllImport("asr_offline_record_sample", EntryPoint = "start_listening", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]static extern IntPtr start_listening(); //释放命令词识别离线引擎[DllImport("asr_offline_record_sample", EntryPoint = "free_msp", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]static extern int free_msp();//test//[DllImport("asr_offline_record_sample", EntryPoint = "test", CharSet = CharSet.Ansi, CallingConvention = CallingConvention.Cdecl)]//public static extern int test();public bool listening_off = false; //监听器循环开启关闭开关public int confidenct = 25; //置信度调节private int tts_off = 0;private float lastTime;private float curTime;void Start(){init_listing();}void Update(){update_listing();}//讲述人///public AudioSource aud;//需要节点关联IEnumerator LoadAudio(string recordPath){WWW www = new WWW(recordPath);yield return www;var clipTemp = www.GetAudioClip();aud.clip = clipTemp;aud.Play();}private void speech_tts(string tts_text){string wav_path = @"C:\\xunfei_speech\\" + tts_text + ".wav";if (File.Exists(wav_path)){StartCoroutine(LoadAudio(wav_path));return;}//如果文件已经生成就不用在合成了，直接读取播放tts_off = loading_tts();if (tts_off == 1){print("初始化朗读成功：" + tts_off);int ret2 = to_speech(wav_path, tts_text);StartCoroutine(LoadAudio(wav_path));}else{print("初始化失败：" + tts_off);}free_tts();}/聆听人////功能：初始化监听器void init_listing(){if (1 == loading_msp()){print("载入初始化成功");//实际应用中只执行一次///if (1 == build_net_msp()){print("下载构建网络命令词成功");if (1 == update_lexicon_msp()){print("更新词典槽成功");}}if (1 == init_run_msp()){print("预热命令词成功");listening_off = true;}}lastTime = Time.time;}//功能：循环发送mic监听器开启，可以重复发送，sdk 做了同步处理//返回：xml格式数据string update_listing(){string restr = "0";curTime = Time.time;if (curTime - lastTime >= 1){if (listening_off){IntPtr ip = start_listening();restr = Marshal.PtrToStringUni(ip);print("打开麦克风监听中..." + restr);get_result_confidenct(restr);//解析xml}// print(curTime - lastTime);lastTime = curTime;}return restr;}//功能：释放监听器void OnDestroy(){free_msp();print("退出了");} //功能：语音识别结果返回xml解析//传入：xml字符串；//返回：置信度结果，是一个0~1的浮点类型数字；double get_result_confidenct(string strxml){// string strxml = @"<?xml version='1.0' encoding='gb2312' standalone='yes' ?><nlp> <version>1.1</version> <rawtext>您好</rawtext> <confidence>27</confidence> <engine>local</engine> <result> <focus>您好</focus> <confidence>18</confidence> <object> <您好 id='65535'>您好</您好> </object> </result></nlp>";if (Equals(strxml,"0")) { return 0; } //输入不是xml过滤掉 直接 返回结果；XmlDocument xml = new XmlDocument();XmlReaderSettings set = new XmlReaderSettings();set.IgnoreComments = true;xml.LoadXml(strxml);int s_confidenct = 0;string s_rawtext = "";int d_confidenct = 0;string d_focus = "";double res = 0;XmlNodeList sour_xmlNodeList = xml.SelectSingleNode("nlp").ChildNodes;foreach (XmlElement node in sour_xmlNodeList){if (node.Name == "confidence"){s_confidenct = int.Parse(node.InnerText.Trim());print(node.Name + ":" + s_confidenct);}if (node.Name == "rawtext"){s_rawtext = node.InnerText.Trim();print(node.Name + ":" + s_rawtext);}}XmlNodeList back_dst_xmlNodeList = xml.SelectSingleNode("nlp").SelectSingleNode("result").ChildNodes;foreach (XmlElement node in back_dst_xmlNodeList){if (node.Name == "confidence"){d_confidenct = int.Parse(node.InnerText.Trim());print(node.Name + ":" + d_confidenct);}if (node.Name == "focus"){d_focus = node.InnerText.Trim();print(node.Name + ":" + d_focus);}}if (s_confidenct > confidenct)//识别置信度调节{send_speech_result(d_focus, s_confidenct);}return res; //返回匹配相似度；}//功能：向父脚本子脚本广播识别结果//传入：1.结果文本|2.置信度|3.计算的匹配率 0~1 之间的浮点数void send_speech_result(string focus, int percent){listening_off = false;free_msp();//临时退出登录if (Equals(focus, "小微") || Equals(focus, "小微小微")){speech_tts("在的");init_listing();return;}speech_tts(focus);init_listing();//以下是将语音识别结果广播给其他节点object[] message = new object[2];message[0] = focus;message[1] = percent;this.gameObject.SendMessage("speech_result", message, SendMessageOptions.DontRequireReceiver);this.gameObject.BroadcastMessage("speech_result", message, SendMessageOptions.DontRequireReceiver);}/}
4.Unity创建 节点1 2D Sprinte 节点2 Audio Audio source 将节点2拖拽到节点1 Inspector面板 Aud节点实现引用关联。
5.该应用使用命令词实现了类似本地唤醒功能，软件运行后一直update 麦克风，监听到命令响应在的 或做其他命令处理。
6.语音合成WAV文件，做了本地保存，反复调用直接读取本地文件，不用反复使用TTS作文字到语音的转换，以节省资源。
步骤九
巴科斯范式.bnf文件可以关注这里巴科斯范式详解，这里简化了命令词定义用于测试。
#BNF+IAT 1.0;
!grammar call;!start <callstart>;
<callstart>:syj|小微小微|小微|向前走|下一步|hello|你好|您
好|小螺丝|星际迷航|大陆|今天太冷了;步骤九
问题总结
1，两个离线引擎不能同时运行，所以上面实现的是交替运行模式 就是识别模块运行，朗读模块初始化会失败，反之亦然，这样导致灵活性不强，不确定问题在哪里，也可能是引用了一个msc_x64.dll文件，这里不太确定，unity目录引用原因未能做测试，期待解决方案。
2.离线命令词识别返回结果会有1-3秒的识别反应时间，才能返回结果 ，这个时间可以做一个语音回馈，但是没有返回结果就不能确定是否应该触发语音回馈，期待解决方案。
3.语音合成朗读速度很快，可以放心使用。
4.以上测试文件打包，有需要可以自行下载。
https://download.csdn.net/download/lijiefu123456/13098984
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