NMTKD
/
translation
/tools
/mosesdecoder
/moses
/TranslationModel
/fuzzy-match
/FuzzyMatchWrapper.cpp
// | |
// FuzzyMatchWrapper.cpp | |
// moses | |
// | |
// Created by Hieu Hoang on 26/07/2012. | |
// Copyright 2012 __MyCompanyName__. All rights reserved. | |
// | |
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) | |
{ | |
cerr << "creating suffix array" << endl; | |
suffixArray = new tmmt::SuffixArray( sourcePath ); | |
//cerr << "loading source data" << endl; | |
//load_corpus(sourcePath, source); | |
cerr << "loading target data" << endl; | |
load_target(targetPath, targetAndAlignment); | |
cerr << "loading alignment" << endl; | |
load_alignment(alignmentPath, targetAndAlignment); | |
// create suffix array | |
//load_corpus(m_config[0], input); | |
cerr << "loading completed" << endl; | |
} | |
string FuzzyMatchWrapper::Extract(long translationId, const string &dirNameStr) | |
{ | |
const Moses::StaticData &staticData = Moses::StaticData::Instance(); | |
WordIndex wordIndex; | |
string fuzzyMatchFile = ExtractTM(wordIndex, translationId, 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()); | |
cmd = "/Users/hieuhoang/unison/workspace/github/moses-smt/bin"; | |
cmd = "/home/hieu/workspace/github/moses-smt/bin"; | |
cmd = staticData.GetBinDirectory(); | |
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(WordIndex &wordIndex, long translationId, const string &dirNameStr) | |
{ | |
const std::vector< std::vector< WORD_ID > > &source = suffixArray->GetCorpus(); | |
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(int start=0; start<input[sentenceInd].size(); start++) { | |
SuffixArray::INDEX prior_first_match = 0; | |
SuffixArray::INDEX prior_last_match = suffixArray->GetSize()-1; | |
vector< string > substring; | |
bool stillMatched = true; | |
vector< pair< SuffixArray::INDEX, SuffixArray::INDEX > > matchedAtThisStart; | |
//cerr << "start: " << start; | |
for(size_t word=start; stillMatched && word<input[sentenceInd].size(); word++) { | |
substring.push_back( GetVocabulary().GetWord( input[sentenceInd][word] ) ); | |
// only look up, if needed (i.e. no unnecessary short gram lookups) | |
// if (! word-start+1 <= short_match_max_length( input_length ) ) | |
// { | |
SuffixArray::INDEX first_match, last_match; | |
stillMatched = false; | |
if (suffixArray->FindMatches( 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++) { | |
size_t 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(wordIndex, translationId, 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(wordIndex, translationId, 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(size_t m=0; m<match.size(); m++) { | |
if (match[m].min_cost <= best_cost) // makes no difference | |
words_matched += match[m].input_end - match[m].input_start + 1; | |
} | |
if (max(input_length,tm_length) - words_matched > 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(size_t p=0; p<pruned.size(); p++) { | |
words_matched += pruned[p].input_end - pruned[p].input_start + 1; | |
} | |
if (max(input_length,tm_length) - words_matched > 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 += GetVocabulary().GetWord(input[sentenceInd][pos]) + " "; | |
} | |
// do not try to find the best ... report multiple matches | |
if (multiple_flag) { | |
for(size_t si=0; si<best_tm.size(); si++) { | |
int s = best_tm[si]; | |
string path; | |
sed( input[sentenceInd], source[s], path, true ); | |
const vector<WORD_ID> &sourceSentence = source[s]; | |
vector<SentenceAlignment> &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; | |
unsigned int best_letter_cost; | |
if (lsed_flag) { | |
best_letter_cost = compute_length( input[sentenceInd] ) * min_match / 100 + 1; | |
for(size_t si=0; si<best_tm.size(); si++) { | |
int s = best_tm[si]; | |
string path; | |
unsigned int letter_cost = sed( input[sentenceInd], source[s], path, true ); | |
if (letter_cost < best_letter_cost) { | |
best_letter_cost = letter_cost; | |
best_path = path; | |
best_match = s; | |
} | |
} | |
} | |
// if letter sed turned off, just compute path for first match | |
else { | |
if (best_tm.size() > 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) { | |
UTIL_THROW_IF2(source.size() == 0, "Empty source phrase"); | |
best_match = 0; | |
} | |
// creat xml & extracts | |
const vector<WORD_ID> &sourceSentence = source[best_match]; | |
vector<SentenceAlignment> &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; | |
string line; | |
while(getline(*fileStreamP, line)) { | |
corpus.push_back( GetVocabulary().Tokenize( line.c_str() ) ); | |
} | |
} | |
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 = GetVocabulary().StoreIfNew("|||"); | |
int lineNum = 0; | |
string line; | |
while(getline(*fileStreamP, line)) { | |
vector<WORD_ID> toks = GetVocabulary().Tokenize( line.c_str() ); | |
corpus.push_back(vector< SentenceAlignment >()); | |
vector< SentenceAlignment > &vec = corpus.back(); | |
vec.push_back(SentenceAlignment()); | |
SentenceAlignment *sentence = &vec.back(); | |
const WORD &countStr = GetVocabulary().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 = GetVocabulary().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; | |
string line; | |
while(getline(*fileStreamP, line)) { | |
vector< SentenceAlignment > &vec = corpus[lineNum]; | |
size_t targetInd = 0; | |
SentenceAlignment *sentence = &vec[targetInd]; | |
vector<string> 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<int> alignPoint = Moses::Tokenize<int>(tok, "-"); | |
assert(alignPoint.size() == 2); | |
sentence->alignment.push_back(pair<int,int>(alignPoint[0], alignPoint[1])); | |
} | |
} | |
++lineNum; | |
} | |
} | |
bool FuzzyMatchWrapper::GetLSEDCache(const std::pair< WORD_ID, WORD_ID > &key, unsigned int &value) const | |
{ | |
boost::shared_lock<boost::shared_mutex> read_lock(m_accessLock); | |
map< pair< WORD_ID, WORD_ID >, unsigned int >::const_iterator lookup = m_lsed.find( key ); | |
if (lookup != m_lsed.end()) { | |
value = lookup->second; | |
return true; | |
} | |
return false; | |
} | |
void FuzzyMatchWrapper::SetLSEDCache(const std::pair< WORD_ID, WORD_ID > &key, const unsigned int &value) | |
{ | |
boost::unique_lock<boost::shared_mutex> lock(m_accessLock); | |
m_lsed[ key ] = value; | |
} | |
/* 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 ); | |
unsigned int value; | |
bool ret = GetLSEDCache(pIdx, value); | |
if (ret) { | |
return value; | |
} | |
// get surface strings for word indices | |
const string &a = GetVocabulary().GetWord( aIdx ); | |
const string &b = GetVocabulary().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 | |
SetLSEDCache(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] += GetVocabulary().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] += GetVocabulary().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 += GetVocabulary().GetWord( a[i-1] ).size(); | |
del += GetVocabulary().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<sentence.size(); i++ ) { | |
length += GetVocabulary().GetWord( sentence[i] ).size(); | |
} | |
return length; | |
} | |
/* brute force method: compare input to all corpus sentences */ | |
void FuzzyMatchWrapper::basic_fuzzy_match( vector< vector< WORD_ID > > source, | |
vector< vector< WORD_ID > > input ) | |
{ | |
// go through input set... | |
for(unsigned int i=0; i<input.size(); i++) { | |
bool use_letter_sed = false; | |
// compute sentence length and worst allowed cost | |
unsigned int input_length; | |
if (use_letter_sed) { | |
input_length = compute_length( input[i] ); | |
} else { | |
input_length = input[i].size(); | |
} | |
unsigned int best_cost = input_length * (100-min_match) / 100 + 2; | |
string best_path = ""; | |
//int best_match = -1; | |
// go through all corpus sentences | |
for(unsigned int s=0; s<source.size(); s++) { | |
int source_length; | |
if (use_letter_sed) { | |
source_length = compute_length( source[s] ); | |
} else { | |
source_length = source[s].size(); | |
} | |
int diff = abs((int)source_length - (int)input_length); | |
if (length_filter_flag && (diff >= 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(WordIndex &wordIndex, long translationId, const vector< WORD_ID > &input ) | |
{ | |
int max_length = short_match_max_length( input.size() ); | |
if (max_length == 0) | |
return; | |
wordIndex.clear(); | |
// store input words and their positions in hash map | |
for(size_t i=0; i<input.size(); i++) { | |
if (wordIndex.find( input[i] ) == wordIndex.end()) { | |
vector< int > position_vector; | |
wordIndex[ input[i] ] = position_vector; | |
} | |
wordIndex[ input[i] ].push_back( i ); | |
} | |
} | |
/* add all short matches to list of matches for a sentence */ | |
void FuzzyMatchWrapper::add_short_matches(WordIndex &wordIndex, long translationId, 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<tm.size(); t_pos++) { | |
input_word_hit = wordIndex.find( tm[t_pos] ); | |
if (input_word_hit != wordIndex.end()) { | |
vector< int > &position_vector = input_word_hit->second; | |
for(size_t j=0; j<position_vector.size(); j++) { | |
int &i_pos = position_vector[j]; | |
// before match | |
int max_cost = max( i_pos , t_pos ); | |
int min_cost = abs( i_pos - t_pos ); | |
if ( i_pos>0 && 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(size_t i=0; i<match.size(); i++) { | |
this_best_cost = min( this_best_cost, match[i].max_cost ); | |
} | |
// cerr << "\tthis best cost: " << this_best_cost << endl; | |
// bottom up combination of spans | |
vector< vector< Match > > 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(size_t i1 = 0; i1 < first_match.size(); i1++) { | |
for(size_t 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<SentenceAlignment> &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 += GetVocabulary().GetWord(wordId) + " "; | |
} | |
for (size_t targetInd = 0; targetInd < targets.size(); ++targetInd) { | |
const SentenceAlignment &sentenceAlignment = targets[targetInd]; | |
string targetStr = sentenceAlignment.getTargetString(GetVocabulary()); | |
string alignStr = sentenceAlignment.getAlignmentString(); | |
outputFile | |
<< sentenceInd << endl | |
<< cost << endl | |
<< sourceStr << endl | |
<< inputStr << endl | |
<< targetStr << endl | |
<< alignStr << endl | |
<< path << endl | |
<< sentenceAlignment.count << endl; | |
} | |
} | |
} // namespace | |