Classes | Typedefs | Functions
gs.h File Reference

(Not opened to public) Gaussian selector Implentation More...

#include <stdio.h>
#include <s3types.h>
#include <logmath.h>

Go to the source code of this file.

Classes

struct  gs_s
 

Typedefs

typedef struct gs_s gs_t
 

Functions

int32 gs_display (char *file, gs_t *gs)
 
gs_tgs_read (const char *file, logmath_t *logmath)
 
int32 gc_compute_closest_cw (gs_t *gs, float32 *feat)
 
int32 gs_mgau_shortlist (gs_t *gs, int32 m, int32 n, float32 *feat, int32 bst_codeid)
 

Detailed Description

(Not opened to public) Gaussian selector Implentation

Implementation of Bochierri 93's idea of Gaussian Selection. A pre-computed Gaussian selector map (not distributed in Sphinx 3 but in s3fast.tgz distributed in Arthur Chan's web page) encode the closest neighbors of a given codeword and a given GMM.

In decoding, the closest codeword of the feature is first found and the nearest neighborhood(s) for all GMMs will be retrieved from the Gaussian selector map.

The reason why this file is not opened to the public is because sub-vector quantization supersed this idea conceptually. Although our SVQ implementation do not assume multiple Gaussians to be computed given a sub-stream(sub-vector) codeword is found. It is not difficult to extend the implementation to accomplish that.

Saying this, for implementation symmetry, we should still check in the Gaussian selector implementation in this archive.

Typedef Documentation

◆ gs_t

typedef struct gs_s gs_t

Function Documentation

◆ gc_compute_closest_cw()

int32 gc_compute_closest_cw ( gs_t gs,
float32 *  feat 
)

Choose the closet Gaussian codebook to use

Parameters
gsgaussain selector
featfeature

◆ gs_display()

int32 gs_display ( char *  file,
gs_t gs 
)

display the Gaussian selector

Parameters
filefile to display
gsThe structure of the gaussian selector

◆ gs_mgau_shortlist()

int32 gs_mgau_shortlist ( gs_t gs,
int32  m,
int32  n,
float32 *  feat,
int32  bst_codeid 
)

Find the short list of the Gaussian selector

Parameters
gsgaussain selector
mmixture index
nnumber of mixtures
featfeature vector
bst_codeidbest code indx

◆ gs_read()

gs_t* gs_read ( const char *  file,
logmath_t *  logmath 
)

Read the Gaussian selector

Parameters
filea file to display