int
feat_free(feat_t * f)
{
if (f == 0)
return 0;
if (--f->refcount > 0)
return f->refcount;
if (f->cepbuf)
ckd_free_2d((void **) f->cepbuf);
ckd_free(f->tmpcepbuf);
if (f->name) {
ckd_free((void *) f->name);
}
if (f->lda)
ckd_free_3d((void ***) f->lda);
ckd_free(f->stream_len);
ckd_free(f->sv_len);
ckd_free(f->sv_buf);
subvecs_free(f->subvecs);
cmn_free(f->cmn_struct);
agc_free(f->agc_struct);
ckd_free(f);
return 0;
}
int
feat_set_subvecs(feat_t *fcb, int32 **subvecs)
{
int32 **sv;
int32 n_sv, n_dim, i;
if (subvecs == 0) {
subvecs_free(fcb->subvecs);
ckd_free(fcb->sv_buf);
ckd_free(fcb->sv_len);
fcb->n_sv = 0;
fcb->subvecs = 0;
fcb->sv_len = 0;
fcb->sv_buf = 0;
fcb->sv_dim = 0;
return 0;
}
if (fcb->n_stream != 1) {
E_ERROR("Subvector specifications require single-stream features!");
return -1;
}
n_sv = 0;
n_dim = 0;
for (sv = subvecs; sv && *sv; ++sv) {
int32 *d;
for (d = *sv; d && *d != -1; ++d) {
++n_dim;
}
++n_sv;
}
if (n_dim > (int32)feat_dimension(fcb)) {
E_ERROR("Total dimensionality of subvector specification %d "
"> feature dimensionality %d\n", n_dim, feat_dimension(fcb));
return -1;
}
fcb->n_sv = n_sv;
fcb->subvecs = subvecs;
fcb->sv_len = (uint32*)ckd_calloc(n_sv, sizeof(*fcb->sv_len));
fcb->sv_buf = (mfcc_t*)ckd_calloc(n_dim, sizeof(*fcb->sv_buf));
fcb->sv_dim = n_dim;
for (i = 0; i < n_sv; ++i) {
int32 *d;
for (d = subvecs[i]; d && *d != -1; ++d) {
++fcb->sv_len[i];
}
}
return 0;
}
int32
main(int32 argc, char *argv[])
{
FILE *fpout;
mgau_model_t *mgau;
int32 **subvec;
int32 max_datarows, datarows, datacols, svqrows, svqcols;
float32 **data, **vqmean;
int32 *datamap, *vqmap;
float64 sqerr;
int32 stdev;
int32 i, j, v, m, c;
cmd_ln_t *config;
logmath_t *logmath;
print_appl_info(argv[0]);
cmd_ln_appl_enter(argc, argv, "default.arg", arg);
unlimit();
config = cmd_ln_get();
logmath = logs3_init(cmd_ln_float64_r(config, "-logbase"), 1, cmd_ln_int32_r(config, "-log3table")); /*Report Progress, use log table */
/* Load means/vars but DO NOT precompute variance inverses or determinants */
mgau = mgau_init(cmd_ln_str_r(config, "-mean"),
cmd_ln_str_r(config, "-var"), 0.0 /* no varfloor */ ,
cmd_ln_str_r(config, "-mixw"), cmd_ln_float32_r(config, "-mixwfloor"), FALSE, /* No precomputation */
".cont.", MIX_INT_FLOAT_COMP, logmath);
/* Parse subvector spec argument; subvec is null terminated; subvec[x] is -1 terminated */
subvec = parse_subvecs(cmd_ln_str_r(config, "-svspec"));
if (cmd_ln_str_r(config, "-subvq")) {
if ((fpout = fopen(cmd_ln_str_r(config, "-subvq"), "w")) == NULL) {
E_ERROR_SYSTEM("Failed to open output file '%s'", fpout);
return 1;
}
}
else
fpout = stdout;
/* Echo command line to output file */
for (i = 0; i < argc - 1; i++)
fprintf(fpout, "# %s \\\n", argv[i]);
fprintf(fpout, "# %s\n#\n", argv[argc - 1]);
/* Print input and output configurations to output file */
for (v = 0; subvec[v]; v++); /* No. of subvectors */
svqrows = cmd_ln_int32_r(config, "-svqrows");
fprintf(fpout, "VQParam %d %d -> %d %d\n",
mgau_n_mgau(mgau), mgau_max_comp(mgau), v, svqrows);
for (v = 0; subvec[v]; v++) {
for (i = 0; subvec[v][i] >= 0; i++);
fprintf(fpout, "Subvector %d length %d ", v, i);
for (i = 0; subvec[v][i] >= 0; i++)
fprintf(fpout, " %2d", subvec[v][i]);
fprintf(fpout, "\n");
}
fflush(fpout);
/*
* datamap[] for identifying non-0 input vectors that take part in the clustering process:
* datamap[m*max_mean + c] = row index of data[][] containing the copy.
* vqmap[] for mapping vq input data to vq output.
*/
max_datarows = mgau_n_mgau(mgau) * mgau_max_comp(mgau);
datamap = (int32 *) ckd_calloc(max_datarows, sizeof(int32));
vqmap = (int32 *) ckd_calloc(max_datarows, sizeof(int32));
stdev = cmd_ln_int32_r(config, "-stdev");
/* Copy and cluster each subvector */
for (v = 0; subvec[v]; v++) {
E_INFO("Clustering subvector %d\n", v);
for (datacols = 0; subvec[v][datacols] >= 0; datacols++); /* Input subvec length */
svqcols = datacols * 2; /* subvec length after concatenating mean + var */
/* Allocate input/output data areas */
data =
(float32 **) ckd_calloc_2d(max_datarows, svqcols,
sizeof(float32));
vqmean =
(float32 **) ckd_calloc_2d(svqrows, svqcols, sizeof(float32));
/* Make a copy of the subvectors from the input data, and initialize maps */
for (i = 0; i < max_datarows; i++)
datamap[i] = -1;
datarows = 0;
for (m = 0; m < mgau_n_mgau(mgau); m++) { /* For each mixture m */
for (c = 0; c < mgau_n_comp(mgau, m); c++) { /* For each component c in m */
if (vector_is_zero
(mgau_var(mgau, m, c), mgau_veclen(mgau))) {
E_INFO("Skipping mgau %d comp %d\n", m, c);
continue;
}
for (i = 0; i < datacols; i++) { /* Copy specified dimensions, mean+var */
data[datarows][i * 2] =
mgau->mgau[m].mean[c][subvec[v][i]];
data[datarows][i * 2 + 1] =
(!stdev) ? mgau->mgau[m].
var[c][subvec[v][i]] : sqrt(mgau->mgau[m].
var[c][subvec[v][i]]);
}
datamap[m * mgau_max_comp(mgau) + c] = datarows++;
}
}
E_INFO("Sanity check: input data[0]:\n");
vector_print(stderr, data[0], svqcols);
for (i = 0; i < max_datarows; i++)
vqmap[i] = -1;
#if 0
{
int32 **in;
printf("Input data: %d x %d\n", datarows, svqcols);
in = (int32 **) data;
for (i = 0; i < datarows; i++) {
printf("%8d:", i);
for (j = 0; j < svqcols; j++)
printf(" %08x", in[i][j]);
printf("\n");
}
for (i = 0; i < datarows; i++) {
printf("%15d:", i);
for (j = 0; j < svqcols; j++)
printf(" %15.7e", data[i][j]);
printf("\n");
}
fflush(stdout);
}
#endif
/* VQ the subvector copy built above */
sqerr = vector_vqgen(data, datarows, svqcols, svqrows,
cmd_ln_float64_r(config, "-eps"), cmd_ln_int32_r(config, "-iter"),
vqmean, vqmap, cmd_ln_int32_r(config, "-seed"));
/* Output VQ */
fprintf(fpout, "Codebook %d Sqerr %e\n", v, sqerr);
for (i = 0; i < svqrows; i++) {
if (stdev) {
/* Convert clustered stdev back to var */
for (j = 1; j < svqcols; j += 2)
vqmean[i][j] *= vqmean[i][j];
}
vector_print(fpout, vqmean[i], svqcols);
}
fprintf(fpout, "Map %d\n", v);
for (i = 0; i < max_datarows; i += mgau_max_comp(mgau)) {
for (j = 0; j < mgau_max_comp(mgau); j++) {
if (datamap[i + j] < 0)
fprintf(fpout, " -1");
else
fprintf(fpout, " %d", vqmap[datamap[i + j]]);
}
fprintf(fpout, "\n");
}
fflush(fpout);
/* Cleanup */
ckd_free_2d((void **) data);
ckd_free_2d((void **) vqmean);
}
subvecs_free(subvec);
ckd_free(datamap);
ckd_free(vqmap);
mgau_free(mgau);
fprintf(fpout, "End\n");
fclose(fpout);
logmath_free(logmath);
cmd_ln_free_r(config);
exit(0);
}
