1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
|
/* -*- c-basic-offset: 4; indent-tabs-mode: nil -*- */
/* ====================================================================
* Copyright (c) 2006 Carnegie Mellon University. All rights
* reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* This work was supported in part by funding from the Defense Advanced
* Research Projects Agency and the National Science Foundation of the
* United States of America, and the CMU Sphinx Speech Consortium.
*
* THIS SOFTWARE IS PROVIDED BY CARNEGIE MELLON UNIVERSITY ``AS IS'' AND
* ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
* THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL CARNEGIE MELLON UNIVERSITY
* NOR ITS EMPLOYEES BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
* DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
* THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* ====================================================================
*
*/
/*
* lda.c -- Read and apply LDA matrices to features.
*
* Author: David Huggins-Daines <dhuggins@cs.cmu.edu>
*/
#include <assert.h>
#include <string.h>
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif
#ifdef _MSC_VER
#pragma warning (disable: 4018)
#endif
#include "sphinxbase/feat.h"
#include "sphinxbase/ckd_alloc.h"
#include "sphinxbase/bio.h"
#include "sphinxbase/err.h"
#define MATRIX_FILE_VERSION "0.1"
int32
feat_read_lda(feat_t *feat, const char *ldafile, int32 dim)
{
FILE *fh;
int32 byteswap;
uint32 chksum, i, m, n;
char **argname, **argval;
assert(feat);
if (feat->n_stream != 1) {
E_ERROR("LDA incompatible with multi-stream features (n_stream = %d)\n",
feat->n_stream);
return -1;
}
if ((fh = fopen(ldafile, "rb")) == NULL) {
E_ERROR_SYSTEM("Failed to open transform file '%s' for reading", ldafile);
return -1;
}
if (bio_readhdr(fh, &argname, &argval, &byteswap) < 0) {
E_ERROR("Failed to read header from transform file '%s'\n", ldafile);
fclose(fh);
return -1;
}
for (i = 0; argname[i]; i++) {
if (strcmp(argname[i], "version") == 0) {
if (strcmp(argval[i], MATRIX_FILE_VERSION) != 0)
E_WARN("%s: Version mismatch: %s, expecting %s\n",
ldafile, argval[i], MATRIX_FILE_VERSION);
}
}
bio_hdrarg_free(argname, argval);
argname = argval = NULL;
chksum = 0;
if (feat->lda)
ckd_free_3d((void ***)feat->lda);
{
/* Use a temporary variable to avoid strict-aliasing problems. */
void ***outlda;
if (bio_fread_3d(&outlda, sizeof(float32),
&feat->n_lda, &m, &n,
fh, byteswap, &chksum) < 0) {
E_ERROR_SYSTEM("%s: bio_fread_3d(lda) failed\n", ldafile);
fclose(fh);
return -1;
}
feat->lda = (void *)outlda;
}
fclose(fh);
#ifdef FIXED_POINT
/* FIXME: This is a fragile hack that depends on mfcc_t and
* float32 being the same size (which they are, but...) */
for (i = 0; i < feat->n_lda * m * n; ++i) {
feat->lda[0][0][i] = FLOAT2MFCC(((float *)feat->lda[0][0])[i]);
}
#endif
/* Note that SphinxTrain stores the eigenvectors as row vectors. */
if (n != feat->stream_len[0])
E_FATAL("LDA matrix dimension %d doesn't match feature stream size %d\n", n, feat->stream_len[0]);
/* Override dim from file if it is 0 or greater than m. */
if (dim > m || dim <= 0) {
dim = m;
}
feat->out_dim = dim;
return 0;
}
void
feat_lda_transform(feat_t *fcb, mfcc_t ***inout_feat, uint32 nfr)
{
mfcc_t *tmp;
uint32 i, j, k;
tmp = ckd_calloc(fcb->stream_len[0], sizeof(mfcc_t));
for (i = 0; i < nfr; ++i) {
/* Do the matrix multiplication inline here since fcb->lda
* is transposed (eigenvectors in rows not columns). */
/* FIXME: In the future we ought to use the BLAS. */
memset(tmp, 0, sizeof(mfcc_t) * fcb->stream_len[0]);
for (j = 0; j < feat_dimension(fcb); ++j) {
for (k = 0; k < fcb->stream_len[0]; ++k) {
tmp[j] += MFCCMUL(inout_feat[i][0][k], fcb->lda[0][j][k]);
}
}
memcpy(inout_feat[i][0], tmp, fcb->stream_len[0] * sizeof(mfcc_t));
}
ckd_free(tmp);
}
|
