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src/sgmm2/am-sgmm2-project.h
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// sgmm2/am-sgmm2-project.h
// Copyright 2012 Johns Hopkins University (author: Daniel Povey)
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#ifndef KALDI_SGMM2_AM_SGMM2_PROJECT_H_
#define KALDI_SGMM2_AM_SGMM2_PROJECT_H_
#include <vector>
#include <queue>
#include "sgmm2/am-sgmm2.h"
namespace kaldi {
class Sgmm2Project {
// This class essentially functions as a namespace for some functions;
// it's a friend of AmSgmm.h. It relates to "predictive" SGMMs. This
// hasn't been written up yet. We don't make any functions const or
// static, because there are no member variables.
public:
// If inv_lda_mllt is the matrix that projects from the space the SGMM is
// in, typically back to the spliced-MFCC space, and begin_dim and end_dim
// represent the range of dims we want to model, then "projection" will be
// a matrix, applied *after* the "inv_lda_mllt" matrix, that projects from
// the raw splice-MFCC features to the space we want to model. This matrix
// is of dimension e.g. 40 x 117, and omits the space that the model's states
// all treat the same.
void ComputeProjection(const AmSgmm2 &sgmm,
const Matrix<BaseFloat> &inv_lda_mllt,
int32 begin_dim,
int32 end_dim, // last dim plus one that we keep.
Matrix<BaseFloat> *projection);
// This function applies the feature-space projection to the SGMM.
// The matrix "total_projection" is the product of the "projection" matrix
// of ComputeProjection times the "inv_lda_mllt" matrix. It actually
// projects from a larger dimension than the current SGMM. We treat
// the means as if extended with zeros, and the covariances as if
// extended with a unit matrix.
void ApplyProjection(const Matrix<BaseFloat> &total_projection,
AmSgmm2 *sgmm);
private:
// Computes statistics for LDA, in the SGMM's feature space.
// This only needs to be approximate, so we use stats based
// on the means in the UBM.
void ComputeLdaStats(const FullGmm &full_ubm,
SpMatrix<double> *between_covar,
SpMatrix<double> *within_covar);
void ProjectVariance (const Matrix<double> &total_projection,
bool inverse,
SpMatrix<double> *variance);
void ProjectVariance (const Matrix<double> &total_projection,
bool inverse,
SpMatrix<float> *variance);
void ComputeLdaTransform(const SpMatrix<double> &B,
const SpMatrix<double> &W,
int32 dim_to_retain,
Matrix<double> *Projection);
};
} // end namespace kaldi
#endif // KALDI_SGMM2_AM_SGMM2_PROJECT_H_
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