diff --git a/src/alignments.cc b/src/alignments.cc
index fd1854f0dcdd5976808b79e8a8a5e45ba1524883..70aaa9d7bab2e6c587e21c312b0a8d313723477f 100644
--- a/src/alignments.cc
+++ b/src/alignments.cc
@@ -3,7 +3,6 @@
#include "modules/sequence_extractors.hh"
#include "modules/sequence_alignment.hh"
#include "modules/similarity_functions.hh"
-#include "modules/decision_resolver.hh"
#include <getopt.h>
#include <cmath>
@@ -27,43 +26,45 @@ std::pair<decoda::Extractor, decoda::Similarity> ExtractorFromString(std::string
if (str == "speaker")
return {decoda::Speaker, decoda::speaker_similarity};
if (str == "responsetime")
- return {decoda::ResponseTime, decoda::response_time_similarity};
+ return {decoda::ResponseTime, decoda::continuous_similarity};
+ if (str == "length")
+ return {decoda::TurnLength, decoda::identity_similarity};
throw std::invalid_argument(str + " is not a valid extractor");
}
void HelpMessage(std::ostream &output, const std::string prog_name) {
- output << "Usage: " << prog_name
- << " [OPTIONS] -x mode -d stem_dir extractor1 [extractor2 ...]"
- << std::endl;
- output << "Options (All):" << std::endl;
- output << "\t-o output -- Main output file (affinity matrix or dictionnary)" << std::endl;
- output << "\t-m dialoguemap -- Output file to store the dialogue mapping in" << std::endl;
- output << "\t-v -- Adds one level to the verbose level" << std::endl;
- output << "\t-i -- The initial gap penality" << std::endl;
- output << "\t-e -- The extended gap penality" << std::endl;
- output << "Options (Mode 0):" << std::endl;
- output << "\t-a align_method -- Alignment method to use (required with mode 0)" << std::endl;
- output << "Options (Mode 1 and 2):" << std::endl;
- output << "\t--perfectmatch -- Only allows perfect matches in dictionnary keys" << std::endl;
- output << "\t--partialmatch -- Allow some gaps and mismatches in dictionnary keys" << std::endl;
- output << "Modes:" << std::endl;
- output << "\t 0: Builds an affinity matrix" << std::endl;
- output << "\t 1: Builds an alignment dictionnary" << std::endl;
- output << "\t 2: Builds vectors for each dialogue" << std::endl;
- output << "Align Methods: 'smithwaterman' or 'needlemanwunsch'" << std::endl;
- output << "Extractors: 'dialogueacts', 'polarity', 'speaker' and 'responsetime'"
- << std::endl;
+ output << "Usage: " << prog_name
+ << " [OPTIONS] -x mode -d stem_dir extractor1 [extractor2 ...]"
+ << std::endl;
+ output << "Options (All):" << std::endl;
+ output << "\t-o output -- Main output file (affinity matrix or dictionnary)" << std::endl;
+ output << "\t-m dialoguemap -- Output file to store the dialogue mapping in" << std::endl;
+ output << "\t-v -- Adds one level to the verbose level" << std::endl;
+ output << "\t-i -- The initial gap penality" << std::endl;
+ output << "\t-e -- The extended gap penality" << std::endl;
+ output << "Options (Mode 0):" << std::endl;
+ output << "\t-a align_method -- Alignment method to use (required with mode 0)" << std::endl;
+ output << "Options (Mode 1 and 2):" << std::endl;
+ output << "\t--perfectmatch -- Only allows perfect matches in dictionnary keys" << std::endl;
+ output << "\t--partialmatch -- Allow some gaps and mismatches in dictionnary keys" << std::endl;
+ output << "Modes:" << std::endl;
+ output << "\t 0: Builds an affinity matrix" << std::endl;
+ output << "\t 1: Builds an alignment dictionnary" << std::endl;
+ output << "\t 2: Builds vectors for each dialogue" << std::endl;
+ output << "Align Methods: 'smithwaterman' or 'needlemanwunsch'" << std::endl;
+ output << "Extractors: 'dialogueacts', 'polarity', 'speaker' and 'length'"
+ << std::endl;
}
void BuildAffinityMatrix(std::vector<decoda::Sequence> &sequences,
- std::vector<decoda::Similarity> &similarity_funcs,
- double init_gap, double extend_gap,
- decoda::AlignmentFunc alignment_func,
- std::ostream &output) {
+ std::vector<decoda::Similarity> &similarity_funcs,
+ double init_gap, double extend_gap,
+ decoda::AlignmentFunc alignment_func,
+ std::ostream &output) {
int nb_dialogues = sequences.size();
- if (!verbose)
+ if (verbose)
std::cerr << "Building affinity matrix..." << std::endl;
int count = 0;
@@ -71,13 +72,13 @@ void BuildAffinityMatrix(std::vector<decoda::Sequence> &sequences,
for (int j = i; j < nb_dialogues; j++) {
if (verbose > 1 && count % 100 == 0) {
std::cerr << "Progress: " << count << "/"
- << (nb_dialogues+1)*nb_dialogues / 2 << "\r";
+ << (nb_dialogues+1)*nb_dialogues / 2 << "\r";
std::cerr.flush();
}
count++;
output << decoda::AlignmentSimilarity(sequences[i], sequences[j],
- similarity_funcs,
- init_gap, extend_gap, alignment_func) << " ";
+ similarity_funcs,
+ init_gap, extend_gap, alignment_func) << " ";
}
output << std::endl;
}
@@ -96,9 +97,9 @@ std::string SequenceToString(const decoda::Sequence &sequence) {
str += "(";
for (auto &value : tuple) {
if (first)
- str += boost::lexical_cast<std::string>(value);
+ str += boost::lexical_cast<std::string>(value);
else
- str += "," + boost::lexical_cast<std::string>(value);
+ str += "," + boost::lexical_cast<std::string>(value);
first = false;
}
str += ")";
@@ -109,7 +110,7 @@ std::string SequenceToString(const decoda::Sequence &sequence) {
}
void AddAlignmentToDictionnary(decoda::Alignment &alignment,
- std::map<decoda::Sequence, int> &dictionnary) {
+ std::map<decoda::Sequence, int> &dictionnary) {
decoda::Sequence sequence;
std::vector<decoda::ExtractorTypes> mismatch;
@@ -142,7 +143,7 @@ void AddAlignmentToDictionnary(decoda::Alignment &alignment,
}
void AddSubAlignmentsToDictionnary(decoda::Alignment &alignment,
- std::map<decoda::Sequence, int> &dictionnary) {
+ std::map<decoda::Sequence, int> &dictionnary) {
int s1_idx = alignment.topleft.first;
decoda::Sequence subsequence;
@@ -152,16 +153,16 @@ void AddSubAlignmentsToDictionnary(decoda::Alignment &alignment,
s1_idx++;
} else {
if (!subsequence.empty()) {
- if (dictionnary.count(subsequence)) {
- dictionnary[subsequence]++;
- } else {
- dictionnary[subsequence] = 1;
- }
+ if (dictionnary.count(subsequence)) {
+ dictionnary[subsequence]++;
+ } else {
+ dictionnary[subsequence] = 1;
+ }
- subsequence.clear();
+ subsequence.clear();
}
if (action == 'D' || action == 'X') {
- s1_idx++;
+ s1_idx++;
}
}
}
@@ -176,12 +177,12 @@ void AddSubAlignmentsToDictionnary(decoda::Alignment &alignment,
}
void BuildAlignmentDictionnary(std::vector<decoda::Sequence> &sequences,
- std::vector<decoda::Similarity> &similarity_funcs,
- double init_gap, double extend_gap, double min_score,
- std::ostream &output, bool perfect_match) {
+ std::vector<decoda::Similarity> &similarity_funcs,
+ double init_gap, double extend_gap, double min_score,
+ std::ostream &output, bool perfect_match) {
size_t nb_dialogues = sequences.size();
- if (!verbose)
+ if (verbose)
std::cerr << "Building dictionnary..." << std::endl;
std::map<decoda::Sequence, int> dictionnary;
@@ -190,19 +191,19 @@ void BuildAlignmentDictionnary(std::vector<decoda::Sequence> &sequences,
for (size_t j = i+1; j < nb_dialogues; ++j) {
if (verbose > 1 && count % 100 == 0) {
std::cerr << "Progress: " << count << "/"
- << (nb_dialogues+1)*nb_dialogues / 2 - nb_dialogues << "\r";
+ << (nb_dialogues+1)*nb_dialogues / 2 - nb_dialogues << "\r";
std::cerr.flush();
}
count++;
std::vector<decoda::Alignment> alignments = decoda::WatermanEggert(sequences[i], sequences[j],
- similarity_funcs,
- init_gap, extend_gap,
- min_score);
+ similarity_funcs,
+ init_gap, extend_gap,
+ min_score);
for (decoda::Alignment &alignment : alignments) {
- if (perfect_match)
- AddSubAlignmentsToDictionnary(alignment, dictionnary);
- else
- AddAlignmentToDictionnary(alignment, dictionnary);
+ if (perfect_match)
+ AddSubAlignmentsToDictionnary(alignment, dictionnary);
+ else
+ AddAlignmentToDictionnary(alignment, dictionnary);
}
}
}
@@ -210,7 +211,7 @@ void BuildAlignmentDictionnary(std::vector<decoda::Sequence> &sequences,
if (verbose > 1)
std::cerr << std::endl << "Done." << std::endl;
- if (!verbose)
+ if (verbose)
std::cerr << "Dictionnary size: " << dictionnary.size() << std::endl;
for (auto &kv : dictionnary) {
@@ -219,34 +220,56 @@ void BuildAlignmentDictionnary(std::vector<decoda::Sequence> &sequences,
}
void AddAlignmentToVectors(decoda::Alignment alignment,
- std::map<decoda::Sequence, std::set<int>> &vectors,
- int dlg1, int dlg2) {
- decoda::Sequence sequence;
+ std::vector<decoda::Similarity> &similarity_funcs,
+ std::map<std::string, std::set<int>> &vectors,
+ int dlg1, int dlg2) {
+ std::string sequence1 = "";
+ std::string sequence2 = "";
-
int s1_idx = alignment.topleft.first;
int s2_idx = alignment.topleft.second;
-
+ bool first = true;
+
for (auto &action : alignment.cigar) {
- switch (action) {
- case 'M': {
- sequence.push_back(alignment.a[s1_idx]);
- s1_idx++;
- s2_idx++;
- break;
- }
+ switch (action) {
+ case 'M':
case 'X': {
- std::vector<decoda::ExtractorTypes> mismatch;
size_t n_extractors = alignment.a[s1_idx].size();
- mismatch.resize(n_extractors);
- for (size_t k = 0; k < n_extractors; ++k) {
- if (alignment.a[s1_idx][k] == alignment.b[s2_idx][k]) {
- mismatch[k] = alignment.a[s1_idx][k];
- } else {
- mismatch[k] = "";
- }
+ if (!first) {
+ sequence1 += ";";
+ sequence2 += ";";
}
- sequence.push_back(mismatch);
+ first = false;
+ sequence1 += "(";
+ sequence2 += "(";
+ for (size_t k = 0; k < n_extractors; k++) {
+ if (similarity_funcs[k] == decoda::continuous_similarity) {
+ double sim = decoda::continuous_similarity(alignment.a[s1_idx][k], alignment.b[s2_idx][k]);
+ if (sim >= 0.0) {
+ long int_a = std::lround(boost::lexical_cast<double>(alignment.a[s1_idx][k]));
+ long int_b = std::lround(boost::lexical_cast<double>(alignment.b[s2_idx][k]));
+
+ sequence1 += std::to_string(int_a);
+ sequence2 += std::to_string(int_b);
+ }
+ } else {
+ if (alignment.a[s1_idx][k] == alignment.b[s2_idx][k]) {
+ std::stringstream ss;
+ ss << alignment.a[s1_idx][k];
+ sequence1 += ss.str();
+ sequence2 += ss.str();
+ }
+ }
+
+ if (k != n_extractors-1) {
+ sequence1 += ",";
+ sequence2 += ",";
+ }
+ }
+
+ sequence1 += ")";
+ sequence2 += ")";
+
s1_idx++;
s2_idx++;
break;
@@ -262,69 +285,142 @@ void AddAlignmentToVectors(decoda::Alignment alignment,
}
}
- vectors[sequence].insert(dlg1);
- vectors[sequence].insert(dlg2);
+ vectors[sequence1].insert(dlg1);
+ vectors[sequence1].insert(dlg2);
+ vectors[sequence2].insert(dlg1);
+ vectors[sequence2].insert(dlg2);
}
void AddSubAlignmentsToVectors(decoda::Alignment alignment,
- std::map<decoda::Sequence, std::set<int>> &vectors,
- int dlg1, int dlg2) {
+ std::vector<decoda::Similarity> &similarity_funcs,
+ std::map<std::string, std::set<int>> &vectors,
+ int dlg1, int dlg2) {
int s1_idx = alignment.topleft.first;
+ int s2_idx = alignment.topleft.second;
- decoda::Sequence subsequence;
+ std::string sequence1 = "";
+ std::string sequence2 = "";
+ bool first = true;
+
for (auto &action : alignment.cigar) {
- if (action == 'M') {
- subsequence.push_back(alignment.a[s1_idx]);
+ if (action == 'M' || action == 'X') {
+ size_t n_extractors = alignment.a[s1_idx].size();
+ std::string substr1 = "(";
+ std::string substr2 = "(";
+ bool completed = true;
+
+ for (size_t k = 0; k < n_extractors; k++) {
+ if (similarity_funcs[k] == decoda::continuous_similarity) {
+ double sim = decoda::continuous_similarity(alignment.a[s1_idx][k], alignment.b[s2_idx][k]);
+ if (sim >= 0.0) {
+ long int_a = std::lround(boost::lexical_cast<double>(alignment.a[s1_idx][k]));
+ long int_b = std::lround(boost::lexical_cast<double>(alignment.b[s2_idx][k]));
+
+ substr1 += std::to_string(int_a);
+ substr2 += std::to_string(int_b);
+ } else {
+ completed = false;
+ break;
+ }
+ } else {
+ if (alignment.a[s1_idx][k] == alignment.b[s2_idx][k]) {
+ std::stringstream ss;
+ ss << alignment.a[s1_idx][k];
+ substr1 += ss.str();
+ substr2 += ss.str();
+ } else {
+ completed = false;
+ break;
+ }
+ }
+
+ if (k != n_extractors-1) {
+ substr1 += ",";
+ substr2 += ",";
+ }
+ }
+ substr1 += ")";
+ substr2 += ")";
+
+ if (completed) {
+ if (!first) {
+ sequence1 += ";";
+ sequence2 += ";";
+ }
+ first = false;
+ sequence1 += substr1;
+ sequence2 += substr2;
+ } else {
+ if (!sequence1.empty()) {
+ vectors[sequence1].insert(dlg1);
+ vectors[sequence1].insert(dlg2);
+ vectors[sequence2].insert(dlg1);
+ vectors[sequence2].insert(dlg2);
+ sequence1.clear();
+ sequence2.clear();
+ }
+ first = true;
+ }
+
s1_idx++;
+ s2_idx++;
} else {
- if (!subsequence.empty()) {
- vectors[subsequence].insert(dlg1);
- vectors[subsequence].insert(dlg2);
-
- subsequence.clear();
+ if (!sequence1.empty()) {
+ vectors[sequence1].insert(dlg1);
+ vectors[sequence1].insert(dlg2);
+ vectors[sequence2].insert(dlg1);
+ vectors[sequence2].insert(dlg2);
+ first = true;
+ sequence1.clear();
+ sequence2.clear();
}
- if (action == 'D' || action == 'X') {
- s1_idx++;
+ if (action == 'D') {
+ s1_idx++;
+ }
+ if (action == 'I') {
+ s2_idx++;
}
}
}
- if (!subsequence.empty()) {
- vectors[subsequence].insert(dlg1);
- vectors[subsequence].insert(dlg2);
+ if (!sequence1.empty()) {
+ vectors[sequence1].insert(dlg1);
+ vectors[sequence1].insert(dlg2);
+ vectors[sequence2].insert(dlg1);
+ vectors[sequence2].insert(dlg2);
}
}
void BuildDialogueVectors(std::vector<decoda::Sequence> &sequences,
- std::vector<decoda::Similarity> &similarity_funcs,
- double init_gap, double extend_gap, double min_score,
- std::ostream &output, bool perfect_match) {
+ std::vector<decoda::Similarity> &similarity_funcs,
+ double init_gap, double extend_gap, double min_score,
+ std::ostream &output, bool perfect_match) {
size_t nb_dialogues = sequences.size();
- if (!verbose)
+ if (verbose)
std::cerr << "Building vectors..." << std::endl;
- std::map<decoda::Sequence, std::set<int>> vectors;
+ std::map<std::string, std::set<int>> vectors;
int count = 0;
for (size_t i = 0; i < nb_dialogues; ++i) {
for (size_t j = i+1; j < nb_dialogues; ++j) {
if (verbose > 1 && count % 100 == 0) {
std::cerr << "Progress: " << count << "/"
- << (nb_dialogues+1)*nb_dialogues / 2 - nb_dialogues << "\r";
+ << (nb_dialogues+1)*nb_dialogues / 2 - nb_dialogues << "\r";
std::cerr.flush();
}
count++;
std::vector<decoda::Alignment> alignments = decoda::WatermanEggert(sequences[i], sequences[j],
- similarity_funcs,
- init_gap, extend_gap,
- min_score);
+ similarity_funcs,
+ init_gap, extend_gap,
+ min_score);
for (decoda::Alignment &alignment : alignments) {
- if (perfect_match) {
- AddSubAlignmentsToVectors(alignment, vectors, i, j);
- } else {
- AddAlignmentToVectors(alignment, vectors, i, j);
- }
+ if (perfect_match) {
+ AddSubAlignmentsToVectors(alignment, similarity_funcs, vectors, i, j);
+ } else {
+ AddAlignmentToVectors(alignment, similarity_funcs, vectors, i, j);
+ }
}
}
}
@@ -333,7 +429,7 @@ void BuildDialogueVectors(std::vector<decoda::Sequence> &sequences,
std::cerr << std::endl << "Done." << std::endl;
for (auto &kv : vectors) {
- output << SequenceToString(kv.first);
+ output << kv.first;
for (int value : vectors[kv.first]) {
output << "\t" << value;
}
@@ -359,18 +455,18 @@ int main(int argc, char *argv[]) {
for (;;) {
static struct option long_options[] =
{
- {"help", no_argument, 0, 'h'},
- {"mode", required_argument, 0, 'x'},
- {"alignmethod", required_argument, 0, 'a'},
- {"dir", required_argument, 0, 'd'},
- {"output", required_argument, 0, 'o'},
- {"dialoguemap", required_argument, 0, 'm'},
- {"perfectmatch", no_argument, &perfect_match, 1},
- {"partialmatch", no_argument, &perfect_match, 0},
- {"verbose", no_argument, 0, 'v'},
- {"init-gap", required_argument, 0, 'i'},
- {"extend-gap", required_argument, 0, 'e'},
- {0, 0, 0, 0}
+ {"help", no_argument, 0, 'h'},
+ {"mode", required_argument, 0, 'x'},
+ {"alignmethod", required_argument, 0, 'a'},
+ {"dir", required_argument, 0, 'd'},
+ {"output", required_argument, 0, 'o'},
+ {"dialoguemap", required_argument, 0, 'm'},
+ {"perfectmatch", no_argument, &perfect_match, 1},
+ {"partialmatch", no_argument, &perfect_match, 0},
+ {"verbose", no_argument, 0, 'v'},
+ {"init-gap", required_argument, 0, 'i'},
+ {"extend-gap", required_argument, 0, 'e'},
+ {0, 0, 0, 0}
};
int option_index = 0;
@@ -408,28 +504,28 @@ int main(int argc, char *argv[]) {
}
case 'x': {
try {
- mode = std::stoi(optarg);
+ mode = std::stoi(optarg);
} catch (std::exception &e) {
- std::cerr << "Argument of -x '" << optarg << "' is not an integer!";
- exit(1);
+ std::cerr << "Argument of -x '" << optarg << "' is not an integer!";
+ exit(1);
}
break;
}
case 'i': {
try {
- init_gap = std::stod(optarg);
+ init_gap = std::stod(optarg);
} catch (std::exception &e) {
- std::cerr << "Argument of -i '" << optarg << "' is not a float!";
- exit(1);
+ std::cerr << "Argument of -i '" << optarg << "' is not a float!";
+ exit(1);
}
break;
}
case 'e': {
try {
- extend_gap = std::stod(optarg);
+ extend_gap = std::stod(optarg);
} catch (std::exception &e) {
- std::cerr << "Argument of -e '" << optarg << "' is not a float!";
- exit(1);
+ std::cerr << "Argument of -e '" << optarg << "' is not a float!";
+ exit(1);
}
break;
}
@@ -477,14 +573,14 @@ int main(int argc, char *argv[]) {
extractors_map.insert({argv[k], ExtractorFromString(argv[k])});
}
- if (!verbose)
+ if (verbose)
std::cerr << "Parsing dialogues..." << std::endl;
decoda::DialogueParser parser(stem_dir);
parser.ReadAll();
if (dialoguemap_set) {
- if (!verbose)
+ if (verbose)
std::cerr << "Outputing dialogue map..." << std::endl;
std::ofstream odialoguemap(dialoguemap);
@@ -495,31 +591,31 @@ int main(int argc, char *argv[]) {
odialoguemap.close();
}
- if (!verbose)
+ if (verbose)
std::cerr << "Number of dialogues: " << parser.dialogues.size() << std::endl;
std::vector<decoda::Extractor> extractors;
std::vector<decoda::Similarity> similarity_funcs;
- if (!verbose) {
+ if (verbose) {
if (mode == 0)
std::cerr << "Alignment method being used: " << align_method << std::endl;
else if (mode == 1)
std::cerr << "Alignment method being used: WatermanEggert" << std::endl;
}
- if (!verbose)
+ if (verbose)
std::cerr << "Extractors being used: ";
for (auto &kv : extractors_map) {
- if (!verbose)
+ if (verbose)
std::cerr << kv.first << " ";
extractors.push_back(kv.second.first);
similarity_funcs.push_back(kv.second.second);
}
- if (!verbose)
+ if (verbose)
std::cerr << std::endl;
- if (!verbose) {
+ if (verbose) {
std::cerr << "Gap penality affine function: " << init_gap << " + " << extend_gap << "*k" << std::endl;
}
diff --git a/src/modules/decision_resolver.hh b/src/modules/decision_resolver.hh
index 2ead1870303700b20053b19daa7b1ccd4238195b..7896b50a81ce43de74683bd71e15c51d49a32366 100644
--- a/src/modules/decision_resolver.hh
+++ b/src/modules/decision_resolver.hh
@@ -8,18 +8,21 @@
namespace decoda {
- typedef std::string (*Resolver)(ExtractorTypes&, ExtractorTypes&);
+ typedef std::string (*Resolver)(ExtractorTypes&, ExtractorTypes&, bool);
- std::string BinaryDecisionResolver(decoda::ExtractorTypes &a, decoda::ExtractorTypes &b) {
+ std::string BinaryDecisionResolver(decoda::ExtractorTypes &a, decoda::ExtractorTypes &b,
+ bool strict) {
if (a == b) return boost::lexical_cast<std::string>(a);
return "";
}
- std::string ContinuousDecisionResolver(decoda::ExtractorTypes &a, decoda::ExtractorTypes &b) {
+ std::string ContinuousDecisionResolver(decoda::ExtractorTypes &a, decoda::ExtractorTypes &b,
+ bool strict=false) {
double double_a = boost::lexical_cast<double>(a);
double double_b = boost::lexical_cast<double>(b);
-
- return std::to_string(std::lround(std::abs(double_a - double_b)));
+ long value = std::lround(std::abs(double_a - double_b));
+ if (!strict)
+ return std::to_string(value);
}
}
diff --git a/src/modules/dialogue_sequencer.cc b/src/modules/dialogue_sequencer.cc
index a7ea8394ad03fe7db84dd4a72dfc1e6edaa40afd..9cdac4a02648746b3655bca835fd4d06ef9c624a 100644
--- a/src/modules/dialogue_sequencer.cc
+++ b/src/modules/dialogue_sequencer.cc
@@ -1,20 +1,27 @@
#include "dialogue_sequencer.hh"
+#include <exception>
namespace decoda {
DialogueSequencer::DialogueSequencer(std::vector<Extractor> extractors) : extractors(extractors) {}
Sequence DialogueSequencer::Transform(Dialogue &dialogue) {
Sequence sequence;
-
+ size_t size = 0;
+
for (Extractor extractor : extractors) {
std::vector<ExtractorTypes> extracted = extractor(dialogue);
if (sequence.empty()) {
- sequence.resize(extracted.size());
+ sequence.resize(extracted.size());
+ size = extracted.size();
}
+
+ if (size != extracted.size()) {
+ throw std::runtime_error("Extractors don't extract sequences of the same length !");
+ }
for (size_t k = 0; k < extracted.size(); ++k) {
- sequence[k].push_back(extracted[k]);
+ sequence[k].push_back(extracted[k]);
}
}
@@ -23,7 +30,7 @@ namespace decoda {
std::vector<Sequence> DialogueSequencer::TransformAll(std::vector<Dialogue> &dialogues) {
std::vector<Sequence> sequences;
-
+
for (Dialogue dialogue : dialogues) {
sequences.push_back(Transform(dialogue));
}
diff --git a/src/modules/sequence_extractors.cc b/src/modules/sequence_extractors.cc
index 78bd9c18e298207c9f376616366072e4232d4862..f35e5bc3005ca91bcf1ffda3b9937d9c31bc63f1 100644
--- a/src/modules/sequence_extractors.cc
+++ b/src/modules/sequence_extractors.cc
@@ -4,96 +4,121 @@
#include <exception>
namespace decoda {
-
std::vector<ExtractorTypes> DialogueActs(Dialogue &dialogue) {
- std::vector<ExtractorTypes> partial_sequence;
-
- for (Turn &turn : dialogue) {
- if (turn[0][kAct] == "//") {
- continue;
- }
-
- std::string act = turn[0][kAct];
- partial_sequence.push_back(act);
- }
-
- return partial_sequence;
+ std::vector<ExtractorTypes> partial_sequence;
+
+ for (Turn &turn : dialogue) {
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
+
+ std::string act = turn[0][kAct];
+ partial_sequence.push_back(act);
+ }
+
+ return partial_sequence;
+ }
+
+ std::vector<ExtractorTypes> TurnLength(Dialogue &dialogue) {
+ std::vector<ExtractorTypes> partial_sequence;
+
+ int length = 0;
+ for (Turn &turn : dialogue) {
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
+ length = turn.size();
+ length = (length-1) / 3;
+ if (length > 5)
+ length = 5;
+ partial_sequence.push_back(length);
+ // length = 0;
+ }
+
+ // if (length != 0) {
+ // length = (length-1) / 3;
+ // if (length > 5)
+ // length = 5;
+ // partial_sequence.push_back(length);
+ // }
+
+ return partial_sequence;
}
std::vector<ExtractorTypes> TurnMeanPolarity(Dialogue &dialogue) {
- std::vector<ExtractorTypes> partial_sequence;
-
- for (Turn &turn : dialogue) {
- if (turn[0][kAct] == "//") {
- continue;
- }
-
- double total_polarity = 0.0;
- int nb_words = turn.size();
- for (Word &word : turn) {
- total_polarity += std::stod(word[kPolarity])*2.5; // unit is 0.4 --> 0.4*2.5 = 1
- }
- double mean = total_polarity / nb_words;
- partial_sequence.push_back(mean);
- }
-
- return partial_sequence;
+ std::vector<ExtractorTypes> partial_sequence;
+
+ for (Turn &turn : dialogue) {
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
+
+ double total_polarity = 0.0;
+ int nb_words = turn.size();
+ for (Word &word : turn) {
+ total_polarity += std::stod(word[kPolarity])*2.5; // unit is 0.4 --> 0.4*2.5 = 1
+ }
+ double mean = total_polarity / nb_words;
+ partial_sequence.push_back(mean);
+ }
+
+ return partial_sequence;
}
std::vector<ExtractorTypes> TurnMeanPolarityDiscrete(Dialogue &dialogue) {
- std::vector<ExtractorTypes> partial_sequence;
-
- for (Turn &turn : dialogue) {
- if (turn[0][kAct] == "//") {
- continue;
- }
-
- double total_polarity = 0.0;
- int nb_words = turn.size();
- for (Word &word : turn) {
- total_polarity += std::stod(word[kPolarity]);
- }
- int mean = nearbyint((total_polarity / nb_words) / 0.4);
- partial_sequence.push_back(mean);
-
- }
-
- return partial_sequence;
+ std::vector<ExtractorTypes> partial_sequence;
+
+ for (Turn &turn : dialogue) {
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
+
+ double total_polarity = 0.0;
+ int nb_words = turn.size();
+ for (Word &word : turn) {
+ total_polarity += std::stod(word[kPolarity]);
+ }
+ int mean = nearbyint((total_polarity / nb_words) / 0.4);
+ partial_sequence.push_back(mean);
+
+ }
+
+ return partial_sequence;
}
std::vector<ExtractorTypes> Speaker(Dialogue &dialogue) {
- std::vector<ExtractorTypes> partial_sequence;
-
- for (Turn &turn : dialogue) {
- if (turn[0][kAct] == "//") {
- continue;
- }
-
- std::string speaker = turn[0][kSpkResolved];
- partial_sequence.push_back(speaker);
- }
-
- return partial_sequence;
+ std::vector<ExtractorTypes> partial_sequence;
+
+ for (Turn &turn : dialogue) {
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
+
+ std::string speaker = turn[0][kSpkResolved];
+ partial_sequence.push_back(speaker);
+ }
+
+ return partial_sequence;
}
std::vector<ExtractorTypes> ResponseTime(Dialogue &dialogue) {
- std::vector<ExtractorTypes> partial_sequence;
+ std::vector<ExtractorTypes> partial_sequence;
- double prev_timestamp = 0.0;
+ double prev_timestamp = 0.0;
- for (Turn &turn : dialogue) {
- double current_timestamp = std::stod(turn[0][kStart]);
- double delay = current_timestamp - prev_timestamp;
- if (prev_timestamp == 0.0) // It's the first turn
- delay = 0.0;
- prev_timestamp = std::stod(turn.back()[kEnd]);
- if (turn[0][kAct] == "//") {
- continue;
- }
+ for (Turn &turn : dialogue) {
+ double current_timestamp = std::stod(turn[0][kStart]);
+ double delay = current_timestamp - prev_timestamp;
+ if (prev_timestamp == 0.0) // It's the first turn
+ delay = 0.0;
+ prev_timestamp = std::stod(turn.back()[kEnd]);
+ if (turn[0][kAct] == "//") {
+ continue;
+ }
- partial_sequence.push_back(delay);
- }
+ partial_sequence.push_back(delay);
+ }
- return partial_sequence;
+ return partial_sequence;
}
}
diff --git a/src/modules/sequence_extractors.hh b/src/modules/sequence_extractors.hh
index 244a8cd36a5706c9e719e67f4fd30ae84c0cd82c..b9da9b732ae6825b8c5d291e216e96dacf63dd8f 100644
--- a/src/modules/sequence_extractors.hh
+++ b/src/modules/sequence_extractors.hh
@@ -14,6 +14,7 @@ namespace decoda {
typedef std::vector<ExtractorTypes> (*Extractor)(Dialogue &dialogue);
std::vector<ExtractorTypes> DialogueActs(Dialogue &dialogue);
+ std::vector<ExtractorTypes> TurnLength(Dialogue &dialogue);
std::vector<ExtractorTypes> TurnMeanPolarity(Dialogue &dialogue);
std::vector<ExtractorTypes> TurnMeanPolarityDiscrete(Dialogue &dialogue);
std::vector<ExtractorTypes> Speaker(Dialogue &dialogue);
diff --git a/src/modules/similarity_functions.cc b/src/modules/similarity_functions.cc
index cce1c22f5dad169e725d9d70a1d05ccb37602c8f..9b50410a8283148a6a0d9d1cd9ee0f5327170a72 100644
--- a/src/modules/similarity_functions.cc
+++ b/src/modules/similarity_functions.cc
@@ -13,16 +13,6 @@ namespace decoda {
return -1.9;
}
- double response_time_similarity(ExtractorTypes &a, ExtractorTypes &b) {
- double double_a = boost::get<double>(a);
- double double_b = boost::get<double>(b);
-
- if (std::abs(double_a - double_b) <= 0.1) {
- return 2;
- }
- return -1;
- }
-
double continuous_similarity(ExtractorTypes &a, ExtractorTypes &b) {
double double_a = boost::get<double>(a);
double double_b = boost::get<double>(b);