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authorMatt A. Tobin <mattatobin@localhost.localdomain>2018-02-02 04:16:08 -0500
committerMatt A. Tobin <mattatobin@localhost.localdomain>2018-02-02 04:16:08 -0500
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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 */