hmm.rar_HMM_HMM 识别_hmm c++_hmm c语言_孤立字HMM识别

//#include "cmhmm.h" int BR_Di/p[MAX_ARCS]; int ME_Disp[MAX_ARCS]; int CO_Disp[MAX_ARCS]; int Train_Disp[MAX_ARCS+MAX_STATES]; int Num_Dimensions; int Num_Train_Sets; int Total_Frames; int Longest_Train; TRAINING Train[MAX_TRAIN_SIZE]; HMM Hmm[MAS_REF]; main(argc,argv) int argc; char *argv[]; { int i,num_ref,result; int cnt[MAX_REF]; string hmm_file; char *in_file=NULL,*ref_list=NULL; char ch_r[MAX_REF][8]; FILE *fp; **************** *命令行参数设置* **************** if(argc<5) { usage(argv[0]); } for(i=1;i<argc;i++) { if(argv[i][0]!='-') { fprintf(stderr,"Illegal switch %s\n",argv[i]); usage(argv[0]); } } switch(argv[i][1]) { case'h': ref_list=argv[++i]; break; case'i': in_file=argv[++i]; break; default: fprint(stderr,"Illegal switch %s\n",argv[i]); usage(argv[0]); break; } ********************************** *读取参考模型的数量，即词表的大小* ********************************** if(fp=fopen(ref_list,"r"))==NULL) { fprint(stedrr,"%s:can't open %s to read.\n",ref_list); exit(0); } fscanf(fp,"%d",&num_ref); **************** *读取模型的参数* ************** for(i=0;i<num_ref;i++) { cnt[i]=0; fscanf(fp,"%s%s",hmm_file,ch_r[i]); read_hmm(hmm_file,i); cal_invdet(i); } fclose(fp); print("Category size:%d\n",num_ref); ********************* *读取待识别的语音数据* ********************* if((Num_Train_Sets=read_training(in_file))>MAX_TRAIN_SIZE) { fprintf(stderr,"%s:too many test patterns in %s.\n",argv[0],in_file); exit(0); } ******* *识别** ****** for(i=0;i<Num_Train_Sets;++i) { result=dp(Train+i,num_ref); ++cnt[result]; #if TRACE printf("[%3d]%3d:%s\n",i+1,Train[i].length,ch_r[result]); fflush(stdout); #endif free(Train[i].data); } printf("###识别结果###"); for(i=0;i<num_ref;i++) { printf("###/%4s/=%6.2f%%\n",ch_r[i],cnt[i]*100/Num_Train_Sets); } usage(obj) char *obj; { fprint(stderr,"Usage:%s-h HMM-list -i input-file\n",obj); exit(0); } #include "cmhmm.h" extern int BR_Disp[],ME_Disp[],CO_Disp[],Train_Disp[]; extern int Total_Frames; extern int Num_Dimensions,Longest_Train; extern TRAINING Train[]; extern HMM Hmm[]; void read_hmm(char *file,int rnum) { FILE *fp; int temp,i,j,k,num,mat_num,from,to,bdisp,mdisp,cdisp; float trans_prob; if((fp=fopen(file,"r"))==NULL) exit(0); if(fscanf(fp,"%d",&Num_Dimensions)==EOF) exit(0); if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_omatrix=temp; if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_mixture=temp; for(i=0;i<Hmm[rnum].num_omatrix;++i) { temp=i*Hmm[rnum].num_mixture; BR_Disp[i]=temp; temp*=Num_Dimensions; ME_Disp[i]=temp; temp*=Num_Dimensions; CO_Disp=temp; } temp=FLOATSIZE*Hmm[rnum].num_omatrix*Hmm[rnum].num_mixture; if((Hmm[rnum].branch_prob=(float*)malloc(temp))==NULL) exit(0); temp*=Num_Dimensions; if(Hmm[rnum].mean=(float*)malloc(temp))==NULL) exit(0); if(Hmm[rnum].covariance=(float*)malloc(temp)==NULL) exit(0); for(i=0;i<Hmm[rnum].num_omatrix;i++) { bdisp=BR_Disp[i]; for(j=0;j<Hmm[rnum].num_mixture;j++) { if(scanf(fp,"%f",Hmm[rnum].branch_prob+bdisp+j)==EOF) exit(0); } } for(temp=0,j=0;j<Hmm[rnum].num_mixture;++j,temp+=Num_Dimensions) { mdisp=ME_Disp[i]+temp; cdisp=CO_Disp[i]+temp*Num_Dimensions; for(k=0;k<Num_Dimensions;k++) if(fscanf(fp,"%f",Hmm[rnum].mean+mdisp+k)==EOF) exit(0); for(k=0;k<Num_Dimensions*Num_Dimensions;k++) if(fscanf(fp,"%f",Hmm[rnum].covariance+cdisp+k)==EOF) exit(0); } if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_states=temp; if((Hmm[rnum].states=(STATE*)malloc(sizeof(STATE)*Hmm[rnum].num_sates))==NULL) exit(0); for(i=0;i<Hmm[rnum].num_states;i++) { Hmm[rnum].states[i].label=i; Hmm[rnum].states[i].num_from=Hmm[rnum].states[i].num_to=0; Hmm[rnum].states[i].is_initial=Hmm[rnum].states[i].is_final=FALSE; } if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_initial=temp; for(i=0;i<Hmm[rnum].num_initial;i++) { if(fscanf(fp,"%d",&num)==EOF) exit(0); Hmm[rnum].states[num].is_initial=TRUE; } if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_final=temp; for(i=0;i<Hmm[rnum].num_final;i++) { if(fscanf(fp,"%d",&num)==EOF) exit(0); Hmm[rnum].states[num].is_final=TRUE; } if(fscanf(fp,"%d",&temp)==EOF) exit(0); Hmm[rnum].num_arcs=temp; if((Hmm[rnum].transitions=(TRANSITION*)malloc(sizeof(TRANSITION)*Hmm[rnum].num_arcs))==NULL) exit(0); for(i=0;i<Hmm[rnum].num_arcs;i++) { if(fscanf(fp,"%d%d%e%d",&from,&to,&trans_prob,&mat_num)==EOF) exit(0); if((mat_num>=Hmm[rnum].num_omatrix)||(mat_num<0)&&(mat_num!=NULL_TRANSITION))) exit(0); if((from>Hmm[rnum].num_states-1)||(from<0)||(to>Hmm[rnum].num_states-1)||(to<0)) { fprintf(stderr,"read_hmm;Illegal from(%d)-to(%d)\n",from,to); exit(0); } if(trans_prob<=0.0) exit(0); Hmm[rnum].transitions[i].trans_prob=log(trans_prob); Hmm[rnum].transitions[i].origin=from; Hmm[rnum].transitions[i].destination=to; Hmm[rnum].transitions[i].out_prob_index=mat_num; Hmm[rnum].states[from].trans_from[Hmm[rnum].states[from].num_from++]=i; Hmm[rnum].states[to].trans_to[Hmm[rnum].states[to].num_to++]=i; if(fscanf(fp,"%*d")!=EOF) exit(0); fclose(fp); } int read_training(char *f_list) { FILE *fp,*fs; int cnt,i,j,k,length,total_length=0,max+0; sring f_name; float buff[100]; if(Num_Dimensions>100) exit(0); if((fs=fopen(f_list,"r"))==NULL) { fprint(stderr,"read_data:can't open %s to read\n",f_list); exit(0); } for(cnt=0;fscanf(fs,"%s",f_name)!=EOF;++cnt) { if(cnt==MAX_TRAIN_SIZE) { printf("Warning in read_data;number of datasets(%s) is forced inte %d.\n",f_list,MAX_TRAIN_SIZE); fflush(stdout); break; } if((fp=fopen(f_name,"rb"))==NULL) exit(0); for(length=0;fread(buff,FLOATSIZE,Num_Dimensions+1,fp)==(Num_Dimensions+1);++length); if((Train[cnt].data=(float*)malloc(FLOATSIZE*Num_Dimensions*length))==NULL) { fprintf(stderr,"read_data:not enough space for %s\n",f_list); exit(EOF); } rewind(fp); for(i=j=0;fread(buff,FLOATSIZE,Num_Dimensions+1,fp)==(Num_Dimensions+1);++i) for(k=1;k<(Num_Dimensions+1);) Train[cnt].data[j++]=100.0*buff[k++]; fclose(fp); if(length!=i) { fprintf(stderr,"read_data:size missmatch(%d!=%d)\n",length,i); exit(EOF); } Train[cnt].length=length; total_length+=length; if(length>max) max=length; } fclose(fs); Total_Frames=total_length; Longest_Train=max; for(i=j=0;j<MAX_ARCS+MAX_STATES;++j,i+=Longest_Train) Train_Disp[j]=i; printf("Training data list:%s[%d data sets]\n",f_list,cnt); return cnt; } /*文件名称cmhmmdp.cpp*/ #include "cmhmm.h" extern int BR_Disp[],ME_Disp[],CO_Disp[],Train_Disp[]; extern int Num_Dimensions,Num_Train_Sets,Longest_Train; extern TRAINING Train[]; extern HMM Hmm[]; extern double *Inv_Covariance[],*Det_Covariance[]; float *data; //dp函数 int dp(TRAINING *train,int num_ref) { char *stop,*cptr; int i,j,k,l,m,s,n,t; int length,index,x; int out,lx,nhat; int Outprob_Disp[MAX_STATES]; double *outprob_buff,oprob; double out_prob,branch_prob,sum_prob; double *pn,*prev_pn,px,p[MAX_REF]; TRANSITION *tptr; length=train->length; data=train->data; //memory allocation for work if((pn=(double *)malloc(Longest_Train*MAX_STATES*DOUBLESIZE))==NULL) exit(0); if((outprob_buff=(double *)malloc((Longest_Train)*MAX_ARCS*DOUBLESIZE))==NULL) exit(0); for(s=i=0;s<MAX_STATES;i+=Longest_Train) Outprob_Disp[s++]=i; for(n=0;n<num_ref;n++) { s=MAX_STATES*Longest_Train; for(i=0;i<s;i++) pn[i]=INFINIT; for(s=0;s<Hmm[n].num_omatrix;++s) if(Hmm[n].states[s].is_initial) pn[Train_Disp[s]]=0.0; } for(i=0;i<MAX_ARCS*Longest_Train;outprob_buff[i++]=INFINIT); for(s=0;s<Hmm[n].num_omatrix;s++) { for(i=0;i<leng