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// Copyright (C) 2003--2004 Darren Moore (moore@idiap.ch)
//
// This file is part of Torch 3.1.
//
// 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.
// 3. The name of the author may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS 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 THE AUTHOR 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 BEAMSEARCHDECODER_INC
#define BEAMSEARCHDECODER_INC
#include "general.h"
#include "DecodingHypothesis.h"
#include "PhoneModels.h"
#include "LinearLexicon.h"
#include "LanguageModel.h"
#include "Vocabulary.h"
#include "log_add.h"
namespace Torch {
/** This class implements a Viterbi decoder with beam search
capabilities. A Lexicon and LanguageModel are required at
creation time (the LanguageModel is optional). By default,
no pruning occurs. Two levels of pruning can be configured -
word interior hypothesis pruning and word end hypothesis pruning.
The application of language model probabilities can be
delayed or performed normally.
@author Darren Moore (moore@idiap.ch)
*/
class BeamSearchDecoder
{
public:
PhoneModels *phone_models ;
LinearLexicon *lexicon ;
LanguageModel *lang_model ;
Vocabulary *vocabulary ;
int n_frames ;
real log_word_entrance_penalty ;
real word_int_beam ;
real word_end_beam ;
DecodingHypothesis ***word_state_hyps_1 ;
DecodingHypothesis ***word_state_hyps_2 ;
DecodingHypothesis **word_end_hyps_1 ;
DecodingHypothesis **word_end_hyps_2 ;
DecodingHypothesis **word_entry_hyps_1 ;
DecodingHypothesis **word_entry_hyps_2 ;
DecodingHypothesis ***curr_word_hyps ;
DecodingHypothesis ***prev_word_hyps ;
DecodingHypothesis **curr_word_entry_hyps ;
DecodingHypothesis **prev_word_entry_hyps ;
DecodingHypothesis **curr_word_end_hyps ;
DecodingHypothesis **prev_word_end_hyps ;
int sent_start_index ;
int sent_end_index ;
bool verbose_mode ;
real max_interior_score ;
DecodingHypothesis *best_word_end_hyp ;
bool delayed_lm ;
/* Constructors/destructor */
BeamSearchDecoder( LinearLexicon *lexicon_ , LanguageModel *lang_model_ ,
real log_word_entrance_penalty_=0.0 , real word_int_beam_=LOG_ZERO ,
real word_end_beam_=LOG_ZERO , bool delayed_lm_=true ,
bool verbose_mode_=false ) ;
virtual ~BeamSearchDecoder() ;
/* Methods */
/// Decodes using the input data vectors in 'input_data'.
/// 'n_frames_' is the number of vectors of input data.
/// 'vec_size' is the number of elements in each vector. The input data can be either
/// features or emission probabilities and 'vec_size' must reflect this.
/// After this function returns, 'num_result_words' contains the number of words
/// recognised and 'result_words' contains the vocabulary indices of the recognised
/// words. The 'result_words' array is allocated inside this function.
void decode( real **input_data , int n_frames_ , int *num_result_words , int **result_words ,
int **result_words_times ) ;
void resetHypotheses() ;
void swapHypBuffers() ;
void processWordInteriorStates() ;
void applyLMProbs() ;
void processWordTransitionsLM( int curr_frame ) ;
void processWordTransitionsNoLM( int curr_frame ) ;
void processWordEntryHypotheses() ;
void init() ;
} ;
}
#endif
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