#include <decodable-simple-looped.h>

Inheritance diagram for DecodableAmNnetSimpleLooped:

Collaboration diagram for DecodableAmNnetSimpleLooped:

[legend]

Public Member Functions
	DecodableAmNnetSimpleLooped (const DecodableNnetSimpleLoopedInfo &info, const TransitionModel &trans_model, const MatrixBase< BaseFloat > &feats, const VectorBase< BaseFloat > ivector=NULL, const MatrixBase< BaseFloat > online_ivectors=NULL, int32 online_ivector_period=1)
	This constructor takes features as input, and you can either supply a single iVector input, estimated in batch-mode ('ivector'), or 'online' iVectors ('online_ivectors' and 'online_ivector_period', or none at all. More...

virtual BaseFloat	LogLikelihood (int32 frame, int32 transition_id)
	Returns the log likelihood, which will be negated in the decoder. More...

virtual int32	NumFramesReady () const
	The call NumFramesReady() will return the number of frames currently available for this decodable object. More...

virtual int32	NumIndices () const
	Returns the number of states in the acoustic model (they will be indexed one-based, i.e. More...

virtual bool	IsLastFrame (int32 frame) const
	Returns true if this is the last frame. More...

Public Member Functions inherited from DecodableInterface
virtual	~DecodableInterface ()

Private Member Functions
	KALDI_DISALLOW_COPY_AND_ASSIGN (DecodableAmNnetSimpleLooped)

Private Attributes
DecodableNnetSimpleLooped	decodable_nnet_

const TransitionModel &	trans_model_

Detailed Description

Definition at line 267 of file decodable-simple-looped.h.

Constructor & Destructor Documentation

◆ DecodableAmNnetSimpleLooped()

DecodableAmNnetSimpleLooped	(	const DecodableNnetSimpleLoopedInfo &	info,
		const TransitionModel &	trans_model,
		const MatrixBase< BaseFloat > &	feats,
		const VectorBase< BaseFloat > *	ivector = `NULL`,
		const MatrixBase< BaseFloat > *	online_ivectors = `NULL`,
		int32	online_ivector_period = `1`
	)

This constructor takes features as input, and you can either supply a single iVector input, estimated in batch-mode ('ivector'), or 'online' iVectors ('online_ivectors' and 'online_ivector_period', or none at all.

Note: it stores references to all arguments to the constructor, so don't delete them till this goes out of scope.

Parameters

[in]	info	This helper class contains all the static pre-computed information this class needs, and contains a pointer to the neural net. If you want prior subtraction to be done, you should have initialized this with the constructor that takes class AmNnetSimple.
[in]	trans_model	The transition model to use. This takes care of the mapping from transition-id (which is an arg to LogLikelihood()) to pdf-id (which is used internally).
[in]	feats	A pointer to the input feature matrix; must be non-NULL. We
[in]	ivector	If you are using iVectors estimated in batch mode, a pointer to the iVector, else NULL.
[in]	ivector	If you are using iVectors estimated in batch mode, a pointer to the iVector, else NULL.
[in]	online_ivectors	If you are using iVectors estimated 'online' a pointer to the iVectors, else NULL.
[in]	online_ivector_period	If you are using iVectors estimated 'online' (i.e. if online_ivectors != NULL) gives the periodicity (in frames) with which the iVectors are estimated.

Definition at line 245 of file decodable-simple-looped.cc.

                                 :
     decodable_nnet_(info, feats, ivector, online_ivectors, online_ivector_period),
     trans_model_(trans_model) { }

Member Function Documentation

◆ IsLastFrame()

virtual bool IsLastFrame ( int32 frame ) const

inlinevirtual

Returns true if this is the last frame.

Frames are zero-based, so the first frame is zero. IsLastFrame(-1) will return false, unless the file is empty (which is a case that I'm not sure all the code will handle, so be careful). Caution: the behavior of this function in an online setting is being changed somewhat. In future it may return false in cases where we haven't yet decided to terminate decoding, but later true if we decide to terminate decoding. The plan in future is to rely more on NumFramesReady(), and in future, IsLastFrame() would always return false in an online-decoding setting, and would only return true in a decoding-from-matrix setting where we want to allow the last delta or LDA features to be flushed out for compatibility with the baseline setup.

Implements DecodableInterface.

Definition at line 313 of file decodable-simple-looped.h.

References KALDI_ASSERT, and KALDI_DISALLOW_COPY_AND_ASSIGN.

                                               {
     KALDI_ASSERT(frame < NumFramesReady());
     return (frame == NumFramesReady() - 1);
   }

◆ KALDI_DISALLOW_COPY_AND_ASSIGN()

KALDI_DISALLOW_COPY_AND_ASSIGN ( DecodableAmNnetSimpleLooped )

private

◆ LogLikelihood()

BaseFloat LogLikelihood	(	int32	frame,
		int32	index
	)

virtual

Returns the log likelihood, which will be negated in the decoder.

The "frame" starts from zero. You should verify that NumFramesReady() > frame before calling this.

Implements DecodableInterface.

Definition at line 255 of file decodable-simple-looped.cc.

References DecodableAmNnetSimpleLooped::decodable_nnet_, DecodableNnetSimpleLooped::GetOutput(), DecodableAmNnetSimpleLooped::trans_model_, and TransitionModel::TransitionIdToPdfFast().

                                                                           {
   int32 pdf_id = trans_model_.TransitionIdToPdfFast(transition_id);
   return decodable_nnet_.GetOutput(frame, pdf_id);
 }

◆ NumFramesReady()

virtual int32 NumFramesReady ( ) const

inlinevirtual

The call NumFramesReady() will return the number of frames currently available for this decodable object.

This is for use in setups where you don't want the decoder to block while waiting for input. This is newly added as of Jan 2014, and I hope, going forward, to rely on this mechanism more than IsLastFrame to know when to stop decoding.

Reimplemented from DecodableInterface.

Definition at line 307 of file decodable-simple-looped.h.

Referenced by main().

                                               {
     return decodable_nnet_.NumFrames();
   }

◆ NumIndices()

virtual int32 NumIndices ( ) const

inlinevirtual

Returns the number of states in the acoustic model (they will be indexed one-based, i.e.

from 1 to NumIndices(); this is for compatibility with OpenFst).

Implements DecodableInterface.

Definition at line 311 of file decodable-simple-looped.h.

311 { return trans_model_.NumTransitionIds(); }

kaldi::nnet3::DecodableAmNnetSimpleLooped::trans_model_

const TransitionModel & trans_model_

Definition: decodable-simple-looped.h:321

kaldi::TransitionModel::NumTransitionIds

int32 NumTransitionIds() const

Returns the total number of transition-ids (note, these are one-based).

Definition: transition-model.h:175

Member Data Documentation

◆ decodable_nnet_

DecodableNnetSimpleLooped decodable_nnet_

private

Definition at line 320 of file decodable-simple-looped.h.

Referenced by DecodableAmNnetSimpleLooped::LogLikelihood().

◆ trans_model_

const TransitionModel& trans_model_

private

Definition at line 321 of file decodable-simple-looped.h.

Referenced by DecodableAmNnetSimpleLooped::LogLikelihood().

The documentation for this class was generated from the following files:

nnet3/decodable-simple-looped.h
nnet3/decodable-simple-looped.cc

Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ DecodableAmNnetSimpleLooped()

Member Function Documentation

◆ IsLastFrame()

◆ KALDI_DISALLOW_COPY_AND_ASSIGN()

◆ LogLikelihood()

◆ NumFramesReady()

◆ NumIndices()

Member Data Documentation

◆ decodable_nnet_

◆ trans_model_