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/* -*- c-basic-offset: 4; indent-tabs-mode: nil -*- */
/* ====================================================================
* Copyright (c) 1999-2004 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.
*
* ====================================================================
*
*/
#ifndef _LIBFBS_GAUDEN_H_
#define _LIBFBS_GAUDEN_H_
/** \file ms_gauden.h
* \brief (Sphinx 3.0 specific) Gaussian density module.
*
* Gaussian density distribution implementation. There are two major
* difference bettwen ms_gauden and cont_mgau. One is the fact that
* ms_gauden only take cares of the Gaussian computation part where
* cont_mgau actually take care of senone computation as well. The
* other is the fact that ms_gauden is a multi-stream implementation
* of GMM computation.
*
*/
/* SphinxBase headers. */
#include <sphinxbase/feat.h>
#include <sphinxbase/logmath.h>
#include <sphinxbase/cmd_ln.h>
/* Local headers. */
#include "vector.h"
#include "pocketsphinx_internal.h"
#include "hmm.h"
#ifdef __cplusplus
extern "C" {
#endif
/**
* \struct gauden_dist_t
* \brief Structure to store distance (density) values for a given input observation wrt density values in some given codebook.
*/
typedef struct {
int32 id; /**< Index of codeword (gaussian density) */
mfcc_t dist; /**< Density value for input observation wrt above codeword;
NOTE: result in logs3 domain, but var_t used for speed */
} gauden_dist_t;
/**
* \struct gauden_t
* \brief Multivariate gaussian mixture density parameters
*/
typedef struct {
mfcc_t ****mean; /**< mean[codebook][feature][codeword] vector */
mfcc_t ****var; /**< like mean; diagonal covariance vector only */
mfcc_t ***det; /**< log(determinant) for each variance vector;
actually, log(sqrt(2*pi*det)) */
logmath_t *lmath; /**< log math computation */
int32 n_mgau; /**< Number codebooks */
int32 n_feat; /**< Number feature streams in each codebook */
int32 n_density; /**< Number gaussian densities in each codebook-feature stream */
int32 *featlen; /**< feature length for each feature */
} gauden_t;
/**
* Read mixture gaussian codebooks from the given files. Allocate memory space needed
* for them. Apply the specified variance floor value.
* Return value: ptr to the model created; NULL if error.
* (See Sphinx3 model file-format documentation.)
*/
gauden_t *
gauden_init (char const *meanfile,/**< Input: File containing means of mixture gaussians */
char const *varfile,/**< Input: File containing variances of mixture gaussians */
float32 varfloor, /**< Input: Floor value to be applied to variances */
logmath_t *lmath
);
/** Release memory allocated by gauden_init. */
void gauden_free(gauden_t *g); /**< In: The gauden_t to free */
/** Transform Gaussians according to an MLLR matrix (or, eventually, more). */
int32 gauden_mllr_transform(gauden_t *s, ps_mllr_t *mllr, cmd_ln_t *config);
/**
* Compute gaussian density values for the given input observation vector wrt the
* specified mixture gaussian codebook (which may consist of several feature streams).
* Density values are left UNnormalized.
* @return 0 if successful, -1 otherwise.
*/
int32
gauden_dist (gauden_t *g, /**< In: handle to entire ensemble of codebooks */
int mgau, /**< In: codebook for which density values to be evaluated
(g->{mean,var}[mgau]) */
int n_top, /**< In: Number top densities to be evaluated */
mfcc_t **obs, /**< In: Observation vector; obs[f] = for feature f */
gauden_dist_t **out_dist
/**< Out: n_top best codewords and density values,
in worsening order, for each feature stream.
out_dist[f][i] = i-th best density for feature f.
Caller must allocate memory for this output */
);
/**
Dump the definitionn of Gaussian distribution.
*/
void gauden_dump (const gauden_t *g /**< In: Gaussian distribution g*/
);
/**
Dump the definition of Gaussian distribution of a particular index to the standard output stream
*/
void gauden_dump_ind (const gauden_t *g, /**< In: Gaussian distribution g*/
int senidx /**< In: The senone index of the Gaussian */
);
#ifdef __cplusplus
}
#endif
#endif /* GAUDEN_H */
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