// // FuzzyMatchWrapper.cpp // moses // // Created by Hieu Hoang on 26/07/2012. // Copyright 2012 __MyCompanyName__. All rights reserved. // #include #include "fuzzy-match/FuzzyMatchWrapper.h" #include "fuzzy-match/SentenceAlignment.h" #include "fuzzy-match/Vocabulary.h" #include "fuzzy-match/Match.h" #include "fuzzy-match/create_xml.h" #include "Util.h" #include "StaticData.h" #include "util/file.hh" using namespace std; namespace tmmt { FuzzyMatchWrapper::FuzzyMatchWrapper(const std::string &sourcePath, const std::string &targetPath, const std::string &alignmentPath) :basic_flag(false) ,lsed_flag(true) ,refined_flag(true) ,length_filter_flag(true) ,parse_flag(true) ,min_match(70) ,multiple_flag(true) ,multiple_slack(0) ,multiple_max(100) { // create suffix array //load_corpus(m_config[0], input); load_corpus(sourcePath, source); load_target(targetPath, targetAndAlignment); load_alignment(alignmentPath, targetAndAlignment); cerr << "creating suffix array" << endl; suffixArray = new tmmt::SuffixArray( sourcePath ); cerr << "done creating suffix array" << endl; } string FuzzyMatchWrapper::Extract(const string &dirNameStr) { const Moses::StaticData &staticData = Moses::StaticData::Instance(); string fuzzyMatchFile = ExtractTM(dirNameStr); // create extrac files create_xml(fuzzyMatchFile); // create phrase table with usual Moses scoring and consolidate programs string cmd; cmd = "LC_ALL=C sort " + fuzzyMatchFile + ".extract | gzip -c > " + fuzzyMatchFile + ".extract.sorted.gz"; system(cmd.c_str()); cmd = "LC_ALL=C sort " + fuzzyMatchFile + ".extract.inv | gzip -c > " + fuzzyMatchFile + ".extract.inv.sorted.gz"; system(cmd.c_str()); #ifdef IS_XCODE cmd = "/Users/hieuhoang/unison/workspace/github/moses-smt/bin"; #elif IS_ECLIPSE cmd = "/home/hieu/workspace/github/moses-smt/bin"; #else cmd = staticData.GetBinDirectory(); #endif cmd += string("/../scripts/training/train-model.perl -dont-zip -first-step 6 -last-step 6 -f en -e fr -hierarchical ") + " -extract-file " + fuzzyMatchFile + ".extract -lexical-file - -score-options \"--NoLex\" " + " -phrase-translation-table " + fuzzyMatchFile + ".pt"; system(cmd.c_str()); return fuzzyMatchFile + ".pt.gz"; } string FuzzyMatchWrapper::ExtractTM(const string &dirNameStr) { string inputPath = dirNameStr + "/in"; string fuzzyMatchFile = dirNameStr + "/fuzzyMatchFile"; ofstream fuzzyMatchStream(fuzzyMatchFile.c_str()); vector< vector< WORD_ID > > input; load_corpus(inputPath, input); assert(input.size() == 1); size_t sentenceInd = 0; clock_t start_clock = clock(); // if (i % 10 == 0) cerr << "."; // establish some basic statistics // int input_length = compute_length( input[i] ); int input_length = input[sentenceInd].size(); int best_cost = input_length * (100-min_match) / 100 + 1; int match_count = 0; // how many substring matches to be considered //cerr << endl << "sentence " << i << ", length " << input_length << ", best_cost " << best_cost << endl; // find match ranges in suffix array vector< vector< pair< SuffixArray::INDEX, SuffixArray::INDEX > > > match_range; for(size_t start=0;startGetSize()-1; vector< string > substring; bool stillMatched = true; vector< pair< SuffixArray::INDEX, SuffixArray::INDEX > > matchedAtThisStart; //cerr << "start: " << start; for(int word=start; stillMatched && wordFindMatches( substring, first_match, last_match, prior_first_match, prior_last_match ) ) { stillMatched = true; matchedAtThisStart.push_back( make_pair( first_match, last_match ) ); //cerr << " (" << first_match << "," << last_match << ")"; //cerr << " " << ( last_match - first_match + 1 ); prior_first_match = first_match; prior_last_match = last_match; } //} } //cerr << endl; match_range.push_back( matchedAtThisStart ); } clock_t clock_range = clock(); map< int, vector< Match > > sentence_match; map< int, int > sentence_match_word_count; // go through all matches, longest first for(int length = input[sentenceInd].size(); length >= 1; length--) { // do not create matches, if these are handled by the short match function if (length <= short_match_max_length( input_length ) ) { continue; } unsigned int count = 0; for(int start = 0; start <= input[sentenceInd].size() - length; start++) { if (match_range[start].size() >= length) { pair< SuffixArray::INDEX, SuffixArray::INDEX > &range = match_range[start][length-1]; // cerr << " (" << range.first << "," << range.second << ")"; count += range.second - range.first + 1; for(SuffixArray::INDEX i=range.first; i<=range.second; i++) { int position = suffixArray->GetPosition( i ); // sentence length mismatch size_t sentence_id = suffixArray->GetSentence( position ); int sentence_length = suffixArray->GetSentenceLength( sentence_id ); int diff = abs( (int)sentence_length - (int)input_length ); // cerr << endl << i << "\tsentence " << sentence_id << ", length " << sentence_length; //if (length <= 2 && input_length>=5 && // sentence_match.find( sentence_id ) == sentence_match.end()) // continue; if (diff > best_cost) continue; // compute minimal cost int start_pos = suffixArray->GetWordInSentence( position ); int end_pos = start_pos + length-1; // cerr << endl << "\t" << start_pos << "-" << end_pos << " (" << sentence_length << ") vs. " // << start << "-" << (start+length-1) << " (" << input_length << ")"; // different number of prior words -> cost is at least diff int min_cost = abs( start - start_pos ); // same number of words, but not sent. start -> cost is at least 1 if (start == start_pos && start>0) min_cost++; // different number of remaining words -> cost is at least diff min_cost += abs( ( sentence_length-1 - end_pos ) - ( input_length-1 - (start+length-1) ) ); // same number of words, but not sent. end -> cost is at least 1 if ( sentence_length-1 - end_pos == input_length-1 - (start+length-1) && end_pos != sentence_length-1 ) min_cost++; // cerr << " -> min_cost " << min_cost; if (min_cost > best_cost) continue; // valid match match_count++; // compute maximal cost int max_cost = max( start, start_pos ) + max( sentence_length-1 - end_pos, input_length-1 - (start+length-1) ); // cerr << ", max_cost " << max_cost; Match m = Match( start, start+length-1, start_pos, start_pos+length-1, min_cost, max_cost, 0); sentence_match[ sentence_id ].push_back( m ); sentence_match_word_count[ sentence_id ] += length; if (max_cost < best_cost) { best_cost = max_cost; if (best_cost == 0) break; } //if (match_count >= MAX_MATCH_COUNT) break; } } // cerr << endl; if (best_cost == 0) break; //if (match_count >= MAX_MATCH_COUNT) break; } // cerr << count << " matches at length " << length << " in " << sentence_match.size() << " tm." << endl; if (best_cost == 0) break; //if (match_count >= MAX_MATCH_COUNT) break; } cerr << match_count << " matches in " << sentence_match.size() << " sentences." << endl; clock_t clock_matches = clock(); // consider each sentence for which we have matches int old_best_cost = best_cost; int tm_count_word_match = 0; int tm_count_word_match2 = 0; int pruned_match_count = 0; if (short_match_max_length( input_length )) { init_short_matches( input[sentenceInd] ); } vector< int > best_tm; typedef map< int, vector< Match > >::iterator I; clock_t clock_validation_sum = 0; for(I tm=sentence_match.begin(); tm!=sentence_match.end(); tm++) { int tmID = tm->first; int tm_length = suffixArray->GetSentenceLength(tmID); vector< Match > &match = tm->second; add_short_matches( match, source[tmID], input_length, best_cost ); //cerr << "match in sentence " << tmID << ": " << match.size() << " [" << tm_length << "]" << endl; // quick look: how many words are matched int words_matched = 0; for(int m=0;m best_cost) { if (length_filter_flag) continue; } tm_count_word_match++; // prune, check again how many words are matched vector< Match > pruned = prune_matches( match, best_cost ); words_matched = 0; for(int p=0;p best_cost) { if (length_filter_flag) continue; } tm_count_word_match2++; pruned_match_count += pruned.size(); int prior_best_cost = best_cost; int cost; clock_t clock_validation_start = clock(); if (! parse_flag || pruned.size()>=10) // to prevent worst cases { string path; cost = sed( input[sentenceInd], source[tmID], path, false ); if (cost < best_cost) { best_cost = cost; } } else { cost = parse_matches( pruned, input_length, tm_length, best_cost ); if (prior_best_cost != best_cost) { best_tm.clear(); } } clock_validation_sum += clock() - clock_validation_start; if (cost == best_cost) { best_tm.push_back( tmID ); } } cerr << "reduced best cost from " << old_best_cost << " to " << best_cost << endl; cerr << "tm considered: " << sentence_match.size() << " word-matched: " << tm_count_word_match << " word-matched2: " << tm_count_word_match2 << " best: " << best_tm.size() << endl; cerr << "pruned matches: " << ((float)pruned_match_count/(float)tm_count_word_match2) << endl; // create xml and extract files string inputStr, sourceStr; for (size_t pos = 0; pos < input_length; ++pos) { inputStr += vocabulary.GetWord(input[sentenceInd][pos]) + " "; } // do not try to find the best ... report multiple matches if (multiple_flag) { int input_letter_length = compute_length( input[sentenceInd] ); for(int si=0; si &sourceSentence = source[s]; vector &targets = targetAndAlignment[s]; create_extract(sentenceInd, best_cost, sourceSentence, targets, inputStr, path, fuzzyMatchStream); } } // if (multiple_flag) else { // find the best matches according to letter sed string best_path = ""; int best_match = -1; int best_letter_cost; if (lsed_flag) { best_letter_cost = compute_length( input[sentenceInd] ) * min_match / 100 + 1; for(int si=0; si 0) { string path; sed( input[sentenceInd], source[best_tm[0]], path, false ); best_path = path; best_match = best_tm[0]; } } cerr << "elapsed: " << (1000 * (clock()-start_clock) / CLOCKS_PER_SEC) << " ( range: " << (1000 * (clock_range-start_clock) / CLOCKS_PER_SEC) << " match: " << (1000 * (clock_matches-clock_range) / CLOCKS_PER_SEC) << " tm: " << (1000 * (clock()-clock_matches) / CLOCKS_PER_SEC) << " (validation: " << (1000 * (clock_validation_sum) / CLOCKS_PER_SEC) << ")" << " )" << endl; if (lsed_flag) { //cout << best_letter_cost << "/" << compute_length( input[sentenceInd] ) << " ("; } //cout << best_cost <<"/" << input_length; if (lsed_flag) { //cout << ")"; } //cout << " ||| " << best_match << " ||| " << best_path << endl; if (best_match == -1) { CHECK(source.size()); best_match = 0; } // creat xml & extracts vector &sourceSentence = source[best_match]; vector &targets = targetAndAlignment[best_match]; create_extract(sentenceInd, best_cost, sourceSentence, targets, inputStr, best_path, fuzzyMatchStream); } // else if (multiple_flag) fuzzyMatchStream.close(); return fuzzyMatchFile; } void FuzzyMatchWrapper::load_corpus( const std::string &fileName, vector< vector< WORD_ID > > &corpus ) { // source ifstream fileStream; fileStream.open(fileName.c_str()); if (!fileStream) { cerr << "file not found: " << fileName << endl; exit(1); } cerr << "loading " << fileName << endl; istream *fileStreamP = &fileStream; char line[LINE_MAX_LENGTH]; while(true) { SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n'); if (fileStreamP->eof()) break; corpus.push_back( vocabulary.Tokenize( line ) ); } } void FuzzyMatchWrapper::load_target(const std::string &fileName, vector< vector< SentenceAlignment > > &corpus) { ifstream fileStream; fileStream.open(fileName.c_str()); if (!fileStream) { cerr << "file not found: " << fileName << endl; exit(1); } cerr << "loading " << fileName << endl; istream *fileStreamP = &fileStream; WORD_ID delimiter = vocabulary.StoreIfNew("|||"); int lineNum = 0; char line[LINE_MAX_LENGTH]; while(true) { SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n'); if (fileStreamP->eof()) break; vector toks = vocabulary.Tokenize( line ); corpus.push_back(vector< SentenceAlignment >()); vector< SentenceAlignment > &vec = corpus.back(); vec.push_back(SentenceAlignment()); SentenceAlignment *sentence = &vec.back(); const WORD &countStr = vocabulary.GetWord(toks[0]); sentence->count = atoi(countStr.c_str()); for (size_t i = 1; i < toks.size(); ++i) { WORD_ID wordId = toks[i]; if (wordId == delimiter) { // target and alignments can have multiple sentences. vec.push_back(SentenceAlignment()); sentence = &vec.back(); // count ++i; const WORD &countStr = vocabulary.GetWord(toks[i]); sentence->count = atoi(countStr.c_str()); } else { // just a normal word, add sentence->target.push_back(wordId); } } ++lineNum; } } void FuzzyMatchWrapper::load_alignment(const std::string &fileName, vector< vector< SentenceAlignment > > &corpus ) { ifstream fileStream; fileStream.open(fileName.c_str()); if (!fileStream) { cerr << "file not found: " << fileName << endl; exit(1); } cerr << "loading " << fileName << endl; istream *fileStreamP = &fileStream; string delimiter = "|||"; int lineNum = 0; char line[LINE_MAX_LENGTH]; while(true) { SAFE_GETLINE((*fileStreamP), line, LINE_MAX_LENGTH, '\n'); if (fileStreamP->eof()) break; vector< SentenceAlignment > &vec = corpus[lineNum]; size_t targetInd = 0; SentenceAlignment *sentence = &vec[targetInd]; vector toks = Moses::Tokenize(line); for (size_t i = 0; i < toks.size(); ++i) { string &tok = toks[i]; if (tok == delimiter) { // target and alignments can have multiple sentences. ++targetInd; sentence = &vec[targetInd]; ++i; } else { // just a normal alignment, add vector alignPoint = Moses::Tokenize(tok, "-"); assert(alignPoint.size() == 2); sentence->alignment.push_back(pair(alignPoint[0], alignPoint[1])); } } ++lineNum; } } /* Letter string edit distance, e.g. sub 'their' to 'there' costs 2 */ unsigned int FuzzyMatchWrapper::letter_sed( WORD_ID aIdx, WORD_ID bIdx ) { // check if already computed -> lookup in cache pair< WORD_ID, WORD_ID > pIdx = make_pair( aIdx, bIdx ); map< pair< WORD_ID, WORD_ID >, unsigned int >::const_iterator lookup = lsed.find( pIdx ); if (lookup != lsed.end()) { return (lookup->second); } // get surface strings for word indices const string &a = vocabulary.GetWord( aIdx ); const string &b = vocabulary.GetWord( bIdx ); // initialize cost matrix unsigned int **cost = (unsigned int**) calloc( sizeof( unsigned int* ), a.size()+1 ); for( unsigned int i=0; i<=a.size(); i++ ) { cost[i] = (unsigned int*) calloc( sizeof(unsigned int), b.size()+1 ); cost[i][0] = i; } for( unsigned int j=0; j<=b.size(); j++ ) { cost[0][j] = j; } // core string edit distance loop for( unsigned int i=1; i<=a.size(); i++ ) { for( unsigned int j=1; j<=b.size(); j++ ) { unsigned int ins = cost[i-1][j] + 1; unsigned int del = cost[i][j-1] + 1; bool match = (a.substr(i-1,1).compare( b.substr(j-1,1) ) == 0); unsigned int diag = cost[i-1][j-1] + (match ? 0 : 1); unsigned int min = (ins < del) ? ins : del; min = (diag < min) ? diag : min; cost[i][j] = min; } } // clear out memory unsigned int final = cost[a.size()][b.size()]; for( unsigned int i=0; i<=a.size(); i++ ) { free( cost[i] ); } free( cost ); // cache and return result lsed[ pIdx ] = final; return final; } /* string edit distance implementation */ unsigned int FuzzyMatchWrapper::sed( const vector< WORD_ID > &a, const vector< WORD_ID > &b, string &best_path, bool use_letter_sed ) { // initialize cost and path matrices unsigned int **cost = (unsigned int**) calloc( sizeof( unsigned int* ), a.size()+1 ); char **path = (char**) calloc( sizeof( char* ), a.size()+1 ); for( unsigned int i=0; i<=a.size(); i++ ) { cost[i] = (unsigned int*) calloc( sizeof(unsigned int), b.size()+1 ); path[i] = (char*) calloc( sizeof(char), b.size()+1 ); if (i>0) { cost[i][0] = cost[i-1][0]; if (use_letter_sed) { cost[i][0] += vocabulary.GetWord( a[i-1] ).size(); } else { cost[i][0]++; } } else { cost[i][0] = 0; } path[i][0] = 'I'; } for( unsigned int j=0; j<=b.size(); j++ ) { if (j>0) { cost[0][j] = cost[0][j-1]; if (use_letter_sed) { cost[0][j] += vocabulary.GetWord( b[j-1] ).size(); } else { cost[0][j]++; } } else { cost[0][j] = 0; } path[0][j] = 'D'; } // core string edit distance algorithm for( unsigned int i=1; i<=a.size(); i++ ) { for( unsigned int j=1; j<=b.size(); j++ ) { unsigned int ins = cost[i-1][j]; unsigned int del = cost[i][j-1]; unsigned int match; if (use_letter_sed) { ins += vocabulary.GetWord( a[i-1] ).size(); del += vocabulary.GetWord( b[j-1] ).size(); match = letter_sed( a[i-1], b[j-1] ); } else { ins++; del++; match = ( a[i-1] == b[j-1] ) ? 0 : 1; } unsigned int diag = cost[i-1][j-1] + match; char action = (ins < del) ? 'I' : 'D'; unsigned int min = (ins < del) ? ins : del; if (diag < min) { action = (match>0) ? 'S' : 'M'; min = diag; } cost[i][j] = min; path[i][j] = action; } } // construct string for best path unsigned int i = a.size(); unsigned int j = b.size(); best_path = ""; while( i>0 || j>0 ) { best_path = path[i][j] + best_path; if (path[i][j] == 'I') { i--; } else if (path[i][j] == 'D') { j--; } else { i--; j--; } } // clear out memory unsigned int final = cost[a.size()][b.size()]; for( unsigned int i=0; i<=a.size(); i++ ) { free( cost[i] ); free( path[i] ); } free( cost ); free( path ); // return result return final; } /* utlility function: compute length of sentence in characters (spaces do not count) */ unsigned int FuzzyMatchWrapper::compute_length( const vector< WORD_ID > &sentence ) { unsigned int length = 0; for( unsigned int i=0; i > source, vector< vector< WORD_ID > > input ) { // go through input set... for(unsigned int i=0;i= best_cost)) { continue; } // compute string edit distance string path; unsigned int cost = sed( input[i], source[s], path, use_letter_sed ); // update if new best if (cost < best_cost) { best_cost = cost; best_path = path; best_match = s; } } //cout << best_cost << " ||| " << best_match << " ||| " << best_path << endl; } } /* definition of short matches very short n-gram matches (1-grams) will not be looked up in the suffix array, since there are too many matches and for longer sentences, at least one 2-gram match must occur */ int FuzzyMatchWrapper::short_match_max_length( int input_length ) { if ( ! refined_flag ) return 0; if ( input_length >= 5 ) return 1; return 0; } /* if we have non-short matches in a sentence, we need to take a closer look at it. this function creates a hash map for all input words and their positions (to be used by the next function) (done here, because this has be done only once for an input sentence) */ void FuzzyMatchWrapper::init_short_matches( const vector< WORD_ID > &input ) { int max_length = short_match_max_length( input.size() ); if (max_length == 0) return; single_word_index.clear(); // store input words and their positions in hash map for(int i=0; i position_vector; single_word_index[ input[i] ] = position_vector; } single_word_index[ input[i] ].push_back( i ); } } /* add all short matches to list of matches for a sentence */ void FuzzyMatchWrapper::add_short_matches( vector< Match > &match, const vector< WORD_ID > &tm, int input_length, int best_cost ) { int max_length = short_match_max_length( input_length ); if (max_length == 0) return; int tm_length = tm.size(); map< WORD_ID,vector< int > >::iterator input_word_hit; for(int t_pos=0; t_pos &position_vector = input_word_hit->second; for(int j=0; j0 && i_pos == t_pos ) min_cost++; // after match max_cost += max( (input_length-i_pos) , (tm_length-t_pos)); min_cost += abs( (input_length-i_pos) - (tm_length-t_pos)); if ( i_pos != input_length-1 && (input_length-i_pos) == (tm_length-t_pos)) min_cost++; if (min_cost <= best_cost) { Match new_match( i_pos,i_pos, t_pos,t_pos, min_cost,max_cost,0 ); match.push_back( new_match ); } } } } } /* remove matches that are subsumed by a larger match */ vector< Match > FuzzyMatchWrapper::prune_matches( const vector< Match > &match, int best_cost ) { //cerr << "\tpruning"; vector< Match > pruned; for(int i=match.size()-1; i>=0; i--) { //cerr << " (" << match[i].input_start << "," << match[i].input_end // << " ; " << match[i].tm_start << "," << match[i].tm_end // << " * " << match[i].min_cost << ")"; //if (match[i].min_cost > best_cost) // continue; bool subsumed = false; for(int j=match.size()-1; j>=0; j--) { if (i!=j // do not compare match with itself && ( match[i].input_end - match[i].input_start <= match[j].input_end - match[j].input_start ) // i shorter than j && ((match[i].input_start == match[j].input_start && match[i].tm_start == match[j].tm_start ) || (match[i].input_end == match[j].input_end && match[i].tm_end == match[j].tm_end) ) ) { subsumed = true; } } if (! subsumed && match[i].min_cost <= best_cost) { //cerr << "*"; pruned.push_back( match[i] ); } } //cerr << endl; return pruned; } /* A* parsing method to compute string edit distance */ int FuzzyMatchWrapper::parse_matches( vector< Match > &match, int input_length, int tm_length, int &best_cost ) { // cerr << "sentence has " << match.size() << " matches, best cost: " << best_cost << ", lengths input: " << input_length << " tm: " << tm_length << endl; if (match.size() == 1) return match[0].max_cost; if (match.size() == 0) return input_length+tm_length; int this_best_cost = input_length + tm_length; for(int i=0;i > multi_match; multi_match.push_back( match ); int match_level = 1; while(multi_match[ match_level-1 ].size()>0) { // init vector vector< Match > empty; multi_match.push_back( empty ); for(int first_level = 0; first_level <= (match_level-1)/2; first_level++) { int second_level = match_level - first_level -1; //cerr << "\tcombining level " << first_level << " and " << second_level << endl; vector< Match > &first_match = multi_match[ first_level ]; vector< Match > &second_match = multi_match[ second_level ]; for(int i1 = 0; i1 < first_match.size(); i1++) { for(int i2 = 0; i2 < second_match.size(); i2++) { // do not combine the same pair twice if (first_level == second_level && i2 <= i1) { continue; } // get sorted matches (first is before second) Match *first, *second; if (first_match[i1].input_start < second_match[i2].input_start ) { first = &first_match[i1]; second = &second_match[i2]; } else { second = &first_match[i1]; first = &second_match[i2]; } //cerr << "\tcombining " // << "(" << first->input_start << "," << first->input_end << "), " // << first->tm_start << " [" << first->internal_cost << "]" // << " with " // << "(" << second->input_start << "," << second->input_end << "), " // << second->tm_start<< " [" << second->internal_cost << "]" // << endl; // do not process overlapping matches if (first->input_end >= second->input_start) { continue; } // no overlap / mismatch in tm if (first->tm_end >= second->tm_start) { continue; } // compute cost int min_cost = 0; int max_cost = 0; // initial min_cost += abs( first->input_start - first->tm_start ); max_cost += max( first->input_start, first->tm_start ); // same number of words, but not sent. start -> cost is at least 1 if (first->input_start == first->tm_start && first->input_start > 0) { min_cost++; } // in-between int skipped_words = second->input_start - first->input_end -1; int skipped_words_tm = second->tm_start - first->tm_end -1; int internal_cost = max( skipped_words, skipped_words_tm ); internal_cost += first->internal_cost + second->internal_cost; min_cost += internal_cost; max_cost += internal_cost; // final min_cost += abs( (tm_length-1 - second->tm_end) - (input_length-1 - second->input_end) ); max_cost += max( (tm_length-1 - second->tm_end), (input_length-1 - second->input_end) ); // same number of words, but not sent. end -> cost is at least 1 if ( ( input_length-1 - second->input_end == tm_length-1 - second->tm_end ) && input_length-1 != second->input_end ) { min_cost++; } // cerr << "\tcost: " << min_cost << "-" << max_cost << endl; // if worst than best cost, forget it if (min_cost > best_cost) { continue; } // add match Match new_match( first->input_start, second->input_end, first->tm_start, second->tm_end, min_cost, max_cost, internal_cost); multi_match[ match_level ].push_back( new_match ); // cerr << "\tstored\n"; // possibly updating this_best_cost if (max_cost < this_best_cost) { // cerr << "\tupdating this best cost to " << max_cost << "\n"; this_best_cost = max_cost; // possibly updating best_cost if (max_cost < best_cost) { // cerr << "\tupdating best cost to " << max_cost << "\n"; best_cost = max_cost; } } } } } match_level++; } return this_best_cost; } void FuzzyMatchWrapper::create_extract(int sentenceInd, int cost, const vector< WORD_ID > &sourceSentence, const vector &targets, const string &inputStr, const string &path, ofstream &outputFile) { string sourceStr; for (size_t pos = 0; pos < sourceSentence.size(); ++pos) { WORD_ID wordId = sourceSentence[pos]; sourceStr += vocabulary.GetWord(wordId) + " "; } for (size_t targetInd = 0; targetInd < targets.size(); ++targetInd) { const SentenceAlignment &sentenceAlignment = targets[targetInd]; string targetStr = sentenceAlignment.getTargetString(vocabulary); string alignStr = sentenceAlignment.getAlignmentString(); outputFile << sentenceInd << endl << cost << endl << sourceStr << endl << inputStr << endl << targetStr << endl << alignStr << endl << path << endl << sentenceAlignment.count << endl; } } } // namespace