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/*
* File: lexdecom.cpp
* Author: Felipe Sánchez-Martínez, Universitat d'Alacant <fsanchez@dlsi.ua.es>
*
* Created on 2010/01/27
*/
#include "lexdecom.h"
#include "scorer-impl.h"
#include <iostream>
#include <fstream>
PhraseScorer*
LexicalDecompositionPhraseScorer::create_scorer(const char *argv[], int &argp, bool reverse, const PhraseScorerFactory &ptf)
{
if(argv[argp] == NULL)
usage();
String lwfile(argv[argp++]);
return new LexicalDecompositionPhraseScorer(ptf.get_phrase_table(), reverse, lwfile, argv, argp, ptf);
}
LexicalDecompositionPhraseScorer::LexicalDecompositionPhraseScorer(PhraseTable &pd, bool reverse,
const String &weightfile, const char *argv[], int &argp,
const PhraseScorerFactory &ptf) :
PhraseScorer(pd, reverse)
{
black_box_scorer = AbsoluteDiscountPhraseScorer::create_scorer(argv, argp, reverse, ptf);
std::ifstream wfile(weightfile.c_str());
//Code copied from LexicalWeightPhraseScorer; it should be factored !! -- 2010/01/27
std::cerr<<"Reading lexical weights from '"<<weightfile<<"' ... ";
while(!wfile.eof()) {
if(wfile.fail()) {
std::cerr << "Problem reading file: " << weightfile << std::endl;
exit(1);
}
String src, tgt;
Score weight;
wfile >> src >> tgt >> weight;
Count src_id = PhraseText::index_word(src);
Count tgt_id = PhraseText::index_word(tgt);
weight_map_.insert(std::make_pair(std::make_pair(src_id, tgt_id), weight));
}
wfile.close();
std::cerr<<"done."<<std::endl;
}
Score
LexicalDecompositionPhraseScorer::get_weight(const String &s_src, const String &s_tgt) const
{
//Code copied from LexicalWeightPhraseScorer; it should be factored !! -- 2010/01/27
Count src = PhraseText::index_word(s_src);
Count tgt = PhraseText::index_word(s_tgt);
return get_weight(src, tgt);
}
inline Score
LexicalDecompositionPhraseScorer::get_weight(Count src, Count tgt) const
{
//Code copied from LexicalWeightPhraseScorer; it should be factored !! -- 2010/01/27
WeightMapType_::const_iterator it = weight_map_.find(std::make_pair(src, tgt));
if(it == weight_map_.end())
return 0.00001; // default value copied from Philipp Koehn's scorer
return it->second;
}
void
LexicalDecompositionPhraseScorer::do_score_phrases()
{
//Estimate p(J|I) = p(src_len|tgt_len)
black_box_scorer->score_phrases();
std::cerr<<"LexicalDecompositionPhraseScorer::do_score_phrases"<<std::endl;
std::map<unsigned, std::map<unsigned, Count> > count_srclen_tgtlen;
std::map<unsigned, Count> total_tgtlen;
for(PhraseTable::iterator it = phrase_table_.begin(); it != phrase_table_.end(); it++) {
const PhrasePairInfo &ppair = *it;
PhraseInfo &src = phrase_table_.get_src_phrase(ppair.get_src());
PhraseInfo &tgt = phrase_table_.get_tgt_phrase(ppair.get_tgt());
unsigned src_len = src.get_phrase().size();
unsigned tgt_len = tgt.get_phrase().size();
/*//Debug code
for (unsigned i=0; i<src_len; i++)
std::cerr<<src.get_phrase().word(i)<<" ";
std::cerr<<"-> "<<src_len<<" ||| ";
for (unsigned i=0; i<tgt_len; i++)
std::cerr<<tgt.get_phrase().word(i)<<" ";
std::cerr<<"-> "<<tgt_len<<std::endl;
*/
count_srclen_tgtlen[src_len][tgt_len]+=ppair.get_count();
total_tgtlen[tgt_len]+=ppair.get_count();
}
std::map<unsigned, std::map<unsigned, Count> >::iterator its;
std::map<unsigned, Count>::iterator itt;
for (its=count_srclen_tgtlen.begin(); its!=count_srclen_tgtlen.end(); its++) {
unsigned src_len=its->first;
for(itt=its->second.begin(); itt!=its->second.end(); itt++) {
unsigned tgt_len=itt->first;
Count cnt=itt->second;
prob_srclen_tgtlen_[src_len][tgt_len] = static_cast<Score>(cnt)/static_cast<Score>(total_tgtlen[tgt_len]);
}
}
}
Score
LexicalDecompositionPhraseScorer::get_noisy_or_combination(Count src_word, PhraseInfo &tgt_phrase)
{
Score sc=1.0;
unsigned tgt_len=tgt_phrase.get_phrase().size();
for(unsigned i=0; i<tgt_len; i++) {
Count tgt_word=tgt_phrase.get_phrase()[i];
sc *= (1.0 - get_weight(src_word, tgt_word));
}
return (1.0 - sc);
}
Score
LexicalDecompositionPhraseScorer::do_get_score(const PhraseTable::const_iterator &it)
{
/*
The implementation of this method relies on the asumption that the
smoothed probabilities produced by AbsoluteDiscountPhraseScorer
are deficient.
*/
PhraseInfo &src_phrase = phrase_table_.get_src_phrase(it->get_src());
PhraseInfo &tgt_phrase = phrase_table_.get_tgt_phrase(it->get_tgt());
unsigned src_len=src_phrase.get_phrase().size();
unsigned tgt_len=tgt_phrase.get_phrase().size();
Score prod=1.0;
for(unsigned j=0; j<src_len; j++)
prod *= get_noisy_or_combination(src_phrase.get_phrase()[j], tgt_phrase);
Score lambda= static_cast<Score>(black_box_scorer->get_discount()) *
tgt_phrase.get_distinct() / tgt_phrase.get_count();
Score ret_value = black_box_scorer->get_score(it) + (lambda * prod * prob_srclen_tgtlen_[src_len][tgt_len]);
/*
//Debug code
for (unsigned i=0; i<src_len; i++)
std::cerr<<src_phrase.get_phrase().word(i)<<" ";
std::cerr<<" ||| ";
for (unsigned i=0; i<tgt_len; i++)
std::cerr<<tgt_phrase.get_phrase().word(i)<<" ";
std::cerr<<"==> discount: "<<black_box_scorer->get_discount()<<"; black box score: "<<black_box_scorer->get_score(it)
<<"; lambda: "<<lambda<<"; prod: "
<<prod<<"; prob_srclen_tgtlen_["<<src_len<<"]["<<tgt_len<<"]: "<<prob_srclen_tgtlen_[src_len][tgt_len]
<<"; count: "<<it->get_count()<<"; score: "<<ret_value;
std::cerr<<std::endl;
*/
return ret_value;
}
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