nnet-example-functions.h File Reference

Note on how to parse this filename: it contains functions relatied to neural-net training examples, mostly discriminative neural-net training examples, i.e. More...

#include "nnet2/nnet-nnet.h"
#include "util/table-types.h"
#include "lat/kaldi-lattice.h"
#include "nnet2/nnet-example.h"
#include "hmm/transition-model.h"
#include "hmm/posterior.h"

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Classes
struct	SplitDiscriminativeExampleConfig
	Config structure for SplitExample, for splitting discriminative training examples. More...
struct	SplitExampleStats
	This struct exists only for diagnostic purposes. More...

Namespaces
	kaldi
	This code computes Goodness of Pronunciation (GOP) and extracts phone-level pronunciation feature for mispronunciations detection tasks, the reference:
	kaldi::nnet2

Functions
bool	LatticeToDiscriminativeExample (const std::vector< int32 > &alignment, const Matrix< BaseFloat > &feats, const CompactLattice &clat, BaseFloat weight, int32 left_context, int32 right_context, DiscriminativeNnetExample *eg)
	Converts lattice to discriminative training example. More...
void	SplitDiscriminativeExample (const SplitDiscriminativeExampleConfig &config, const TransitionModel &tmodel, const DiscriminativeNnetExample &eg, std::vector< DiscriminativeNnetExample > *egs_out, SplitExampleStats *stats_out)
	Split a "discriminative example" into multiple pieces, splitting where the lattice has "pinch points". More...
void	ExciseDiscriminativeExample (const SplitDiscriminativeExampleConfig &config, const TransitionModel &tmodel, const DiscriminativeNnetExample &eg, std::vector< DiscriminativeNnetExample > *egs_out, SplitExampleStats *stats_out)
	Remove unnecessary frames from discriminative training example. More...
void	AppendDiscriminativeExamples (const std::vector< const DiscriminativeNnetExample * > &input, DiscriminativeNnetExample *output)
	Appends the given vector of examples (which must be non-empty) into a single output example (called by CombineExamples, which might be a more convenient interface). More...
void	CombineDiscriminativeExamples (int32 max_length, const std::vector< DiscriminativeNnetExample > &input, std::vector< DiscriminativeNnetExample > *output)
	This function is used to combine multiple discriminative-training examples (each corresponding to a segment of a lattice), into one. More...
void	SolvePackingProblem (BaseFloat max_cost, const std::vector< BaseFloat > &costs, std::vector< std::vector< size_t > > *groups)
	This function solves the "packing problem" using the "first fit" algorithm. More...
void	ExampleToPdfPost (const TransitionModel &tmodel, const std::vector< int32 > &silence_phones, std::string criterion, bool drop_frames, bool one_silence_class, const DiscriminativeNnetExample &eg, Posterior *post)
	Given a discriminative training example, this function works out posteriors at the pdf level (note: these are "discriminative-training posteriors" that may be positive or negative. More...
void	UpdateHash (const TransitionModel &tmodel, const DiscriminativeNnetExample &eg, std::string criterion, bool drop_frames, bool one_silence_class, Matrix< double > *hash, double *num_weight, double *den_weight, double *tot_t)
	This function is used in code that tests the functionality that we provide here, about splitting and excising nnet examples. More...

Detailed Description

Note on how to parse this filename: it contains functions relatied to neural-net training examples, mostly discriminative neural-net training examples, i.e.

type DiscriminativeNnetExample

Definition in file nnet-example-functions.h.