bool asr(speechrecog::Command::Request &req,
speechrecog::Command::Response &res)
{
const char *login_config = "appid = 55b1aeb0"; //登录参数
UserData asr_data;
int ret = 0 ;
char c;
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(&asr_data, 0, sizeof(UserData));
printf("构建离线识别语法网络...\n");
ret = build_grammar(&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");
goto exit;
}
while (1 != asr_data.build_fini)
usleep(300 * 1000);
if (MSP_SUCCESS != asr_data.errcode)
goto exit;
printf("离线识别语法网络构建完成，开始识别...\n");
ret = run_asr(&asr_data);
if (MSP_SUCCESS != ret) {
printf("离线语法识别出错: %d \n", ret);
goto exit;
}
/////////////////////////////将识别结果rec_rslt传递给trigger//////////////////////////////////////////
res.command=rec_rslt;
if(flag1)
res.command=tmpt1;
if(flag2)
res.command=tmpt2;
exit:
MSPLogout();
return true;
}
int main()
{
grammar* g = build_grammar("grammar/simple.txt");
gaussian_cluster* sil = g->hmms[10];
gaussian_cluster* one = g->hmms[1];
gaussian_cluster* two = g->hmms[2];
(void) sil; (void) one; (void) two;
//Print out params in matrix
/*
for(int j = 0; j < CEPSTRUM_DIMENSION; j++)
{
for(int i = 0; i < sil->num_clusters; i++)
printf("%f ",sil->params[i]->means.values[j]);
printf("\n");
}
printf("\n\n");
*/
for(int j = 0; j < CEPSTRUM_DIMENSION; j++)
{
for(int i = 0; i < one->num_clusters; i++)
printf("%f ",one->params[i]->means.values[j]);
printf("\n");
}
printf("\n\n");
/*
for(int j = 0; j < CEPSTRUM_DIMENSION; j++)
{
for(int i = 0; i < two->num_clusters; i++)
printf("%f ",two->params[i]->means.values[j]);
printf("\n");
}
*/
/*
//Append models
gaussian_cluster* cat = malloc(sizeof(gaussian_cluster));
cat->params = calloc(25,sizeof(single_gaussian_params*));
cat->stationary_probs = calloc(25,sizeof(double));
cat->transition_probs = calloc(25,sizeof(double));
cat->num_clusters = 25;
gaussian_cluster* wordone = g->hmms[8];
gaussian_cluster* wordtwo = g->hmms[4];
for(int i = 0; i < 5; i++)
{
cat->params[i] = sil->params[i];
cat->params[i+5] = wordone->params[i];
cat->params[i+10] = sil->params[i];
cat->params[i+15] = wordtwo->params[i];
cat->params[i+20] = sil->params[i];
cat->stationary_probs[i] = sil->stationary_probs[i];
cat->stationary_probs[i+5] = wordone->stationary_probs[i];
cat->stationary_probs[i+10] = sil->stationary_probs[i];
cat->stationary_probs[i+15] = wordtwo->stationary_probs[i];
cat->stationary_probs[i+20] = sil->stationary_probs[i];
cat->transition_probs[i] = sil->transition_probs[i];
cat->transition_probs[i+5] = wordone->transition_probs[i];
cat->transition_probs[i+10] = sil->transition_probs[i];
cat->transition_probs[i+15] = wordtwo->transition_probs[i];
cat->transition_probs[i+20] = sil->transition_probs[i];
}
//Read in test
feature_vectors* test = features_from_file("analysis/eightfour-40.out");
//Score
dtw_t* trellis = *get_gaussian_trellis(test, &cat, 1, false, .1);
while(!dtw_fill_next_col(trellis));
dtw_print_struct(trellis);
*/
return 0;
}
