convert data structure for prefix from map to trie tree

deep_speech_2/deploy.py

@@ -18,7 +18,7 @@ import time
 parser = argparse.ArgumentParser(description=__doc__)
 parser.add_argument(
     "--num_samples",
-    default=32,
+    default=5,
     type=int,
     help="Number of samples for inference. (default: %(default)s)")
 parser.add_argument(
@@ -79,7 +79,7 @@ parser.add_argument(
     "(default: %(default)s)")
 parser.add_argument(
     "--beam_size",
-    default=200,
+    default=20,
     type=int,
     help="Width for beam search decoding. (default: %(default)d)")
 parser.add_argument(
@@ -104,7 +104,7 @@ parser.add_argument(
     help="Parameter associated with word count. (default: %(default)f)")
 parser.add_argument(
     "--cutoff_prob",
-    default=0.99,
+    default=1.0,
     type=float,
     help="The cutoff probability of pruning"
     "in beam search. (default: %(default)f)")
@@ -183,7 +183,8 @@ def infer():
                 vocabulary=data_generator.vocab_list,
                 blank_id=len(data_generator.vocab_list),
                 cutoff_prob=args.cutoff_prob,
-                ext_scoring_func=ext_scorer, )
+                #            ext_scoring_func=ext_scorer,
+            )
             batch_beam_results += [beam_result]
     else:
         batch_beam_results = ctc_beam_search_decoder_batch(

deep_speech_2/deploy/ctc_decoders.cpp

@@ -4,11 +4,13 @@
 #include <utility>
 #include <cmath>
 #include <limits>
+#include "fst/fstlib.h"
 #include "ctc_decoders.h"
 #include "decoder_utils.h"
+#include "path_trie.h"
 #include "ThreadPool.h"
 
-typedef double log_prob_type;
+typedef float log_prob_type;
 
 std::string ctc_best_path_decoder(std::vector<std::vector<double> > probs_seq,
                                   std::vector<std::string> vocabulary)
@@ -89,24 +91,30 @@ std::vector<std::pair<double, std::string> >
         exit(1);
     }
 
-    // initialize
-    // two sets containing selected and candidate prefixes respectively
-    std::map<std::string, log_prob_type> prefix_set_prev, prefix_set_next;
-    // probability of prefixes ending with blank and non-blank
-    std::map<std::string, log_prob_type> log_probs_b_prev, log_probs_nb_prev;
-    std::map<std::string, log_prob_type> log_probs_b_cur, log_probs_nb_cur;
-
-    static log_prob_type NUM_MAX = std::numeric_limits<log_prob_type>::max();
-    prefix_set_prev["\t"] = 0.0;
-    log_probs_b_prev["\t"] = 0.0;
-    log_probs_nb_prev["\t"] = -NUM_MAX;
-
-    for (int time_step=0; time_step<num_time_steps; time_step++) {
-        prefix_set_next.clear();
-        log_probs_b_cur.clear();
-        log_probs_nb_cur.clear();
-        std::vector<double> prob = probs_seq[time_step];
+    static log_prob_type POS_INF = std::numeric_limits<log_prob_type>::max();
+    static log_prob_type NEG_INF = -POS_INF;
+    static log_prob_type NUM_MIN = std::numeric_limits<log_prob_type>::min();
+
+    // init
+    PathTrie root;
+    root._log_prob_b_prev = 0.0;
+    root._score = 0.0;
+    std::vector<PathTrie*> prefixes;
+    prefixes.push_back(&root);
+
+    if ( ext_scorer != nullptr && !ext_scorer->is_character_based()) {
+        if (ext_scorer->dictionary == nullptr) {
+        // TODO: init dictionary
+        }
+        auto fst_dict = static_cast<fst::StdVectorFst*>(ext_scorer->dictionary);
+        fst::StdVectorFst* dict_ptr = fst_dict->Copy(true);
+        root.set_dictionary(dict_ptr);
+        auto matcher = std::make_shared<FSTMATCH>(*dict_ptr, fst::MATCH_INPUT);
+        root.set_matcher(matcher);
+    }
 
+    for (int time_step = 0; time_step < num_time_steps; time_step++) {
+        std::vector<double> prob = probs_seq[time_step];
         std::vector<std::pair<int, double> > prob_idx;
         for (int i=0; i<prob.size(); i++) {
             prob_idx.push_back(std::pair<int, double>(i, prob[i]));
@@ -132,113 +140,134 @@ std::vector<std::pair<double, std::string> >
         std::vector<std::pair<int, log_prob_type> > log_prob_idx;
         for (int i=0; i<cutoff_len; i++) {
             log_prob_idx.push_back(std::pair<int, log_prob_type>
-                        (prob_idx[i].first, log(prob_idx[i].second)));
+                        (prob_idx[i].first, log(prob_idx[i].second + NUM_MIN)));
         }
 
-        // extend prefix
-        for (std::map<std::string, log_prob_type>::iterator
-             it = prefix_set_prev.begin();
-            it != prefix_set_prev.end(); it++) {
-            std::string l = it->first;
-            if( prefix_set_next.find(l) == prefix_set_next.end()) {
-                log_probs_b_cur[l] = log_probs_nb_cur[l] = -NUM_MAX;
-            }
+        // loop over chars
+        for (int index = 0; index < log_prob_idx.size(); index++) {
+            auto c = log_prob_idx[index].first;
+            log_prob_type log_prob_c = log_prob_idx[index].second;
+            //log_prob_type log_probs_prev;
 
-            for (int index=0; index<log_prob_idx.size(); index++) {
-                int c = log_prob_idx[index].first;
-                log_prob_type log_prob_c = log_prob_idx[index].second;
-                log_prob_type log_probs_prev;
+            for (int i = 0; i < prefixes.size() && i<beam_size; i++) {
+                auto prefix = prefixes[i];
+                // blank
                 if (c == blank_id) {
-                    log_probs_prev = log_sum_exp(log_probs_b_prev[l],
-                                                 log_probs_nb_prev[l]);
-                    log_probs_b_cur[l] = log_sum_exp(log_probs_b_cur[l],
-                                                     log_prob_c+log_probs_prev);
-                } else {
-                    std::string last_char = l.substr(l.size()-1, 1);
-                    std::string new_char = vocabulary[c];
-                    std::string l_plus = l + new_char;
-
-                    if( prefix_set_next.find(l_plus) == prefix_set_next.end()) {
-                        log_probs_b_cur[l_plus] = -NUM_MAX;
-                        log_probs_nb_cur[l_plus] = -NUM_MAX;
+                    prefix->_log_prob_b_cur = log_sum_exp(
+                                               prefix->_log_prob_b_cur,
+                                               log_prob_c + prefix->_score);
+                    continue;
+                }
+                // repeated character
+                if (c == prefix->_character) {
+                    prefix->_log_prob_nb_cur = log_sum_exp(
+                        prefix->_log_prob_nb_cur,
+                        log_prob_c + prefix->_log_prob_nb_prev
+                        );
+                }
+                // get new prefix
+                auto prefix_new = prefix->get_path_trie(c);
+
+                if (prefix_new != nullptr) {
+                    float log_p = NEG_INF;
+
+                    if (c == prefix->_character
+                        && prefix->_log_prob_b_prev > NEG_INF) {
+                        log_p = log_prob_c + prefix->_log_prob_b_prev;
+                    } else if (c != prefix->_character) {
+                        log_p = log_prob_c + prefix->_score;
                     }
-                    if (last_char == new_char) {
-                        log_probs_nb_cur[l_plus] = log_sum_exp(
-                                                log_probs_nb_cur[l_plus],
-                                                log_prob_c+log_probs_b_prev[l]
-                                            );
-                        log_probs_nb_cur[l] = log_sum_exp(
-                                                log_probs_nb_cur[l],
-                                                log_prob_c+log_probs_nb_prev[l]
-                                            );
-                    } else if (new_char == " ") {
-                        float score = 0.0;
-                        if (ext_scorer != NULL && l.size() > 1) {
-                            score = ext_scorer->get_score(l.substr(1), true);
+
+                    // language model scoring
+                    if (ext_scorer != nullptr &&
+                        (c == space_id || ext_scorer->is_character_based()) ) {
+                        PathTrie *prefix_to_score = nullptr;
+
+                        // don't score the space
+                        if (ext_scorer->is_character_based()) {
+                            prefix_to_score = prefix_new;
+                        } else {
+                            prefix_to_score = prefix;
                         }
-                        log_probs_prev = log_sum_exp(log_probs_b_prev[l],
-                                                     log_probs_nb_prev[l]);
-                        log_probs_nb_cur[l_plus] = log_sum_exp(
-                                            log_probs_nb_cur[l_plus],
-                                            score + log_prob_c + log_probs_prev
-                                        );
-                    } else {
-                        log_probs_prev = log_sum_exp(log_probs_b_prev[l],
-                                                     log_probs_nb_prev[l]);
-                        log_probs_nb_cur[l_plus] = log_sum_exp(
-                                                    log_probs_nb_cur[l_plus],
-                                                    log_prob_c+log_probs_prev
-                                                );
+
+                        double score = 0.0;
+                        std::vector<std::string> ngram;
+                        ngram = ext_scorer->make_ngram(prefix_to_score);
+                        score = ext_scorer->get_log_cond_prob(ngram) *
+                                ext_scorer->alpha;
+
+                        log_p += score;
+                        log_p += ext_scorer->beta;
+
                     }
-                    prefix_set_next[l_plus] = log_sum_exp(
-                                                log_probs_nb_cur[l_plus],
-                                                log_probs_b_cur[l_plus]
-                                            );
+                    prefix_new->_log_prob_nb_cur = log_sum_exp(
+                                        prefix_new->_log_prob_nb_cur, log_p);
                 }
             }
 
-            prefix_set_next[l] = log_sum_exp(log_probs_b_cur[l],
-                                             log_probs_nb_cur[l]);
+        } // end of loop over chars
+
+        prefixes.clear();
+        // update log probabilities
+        root.iterate_to_vec(prefixes);
+
+        // sort prefixes by score
+        if (prefixes.size() >= beam_size) {
+            std::nth_element(prefixes.begin(),
+                    prefixes.begin() + beam_size,
+                    prefixes.end(),
+                    prefix_compare);
+
+            for (size_t i = beam_size; i < prefixes.size(); i++) {
+                prefixes[i]->remove();
+            }
+        }
+    }
+
+    for (size_t i = 0; i < beam_size && i < prefixes.size(); i++) {
+        double approx_ctc = prefixes[i]->_score;
+
+        // remove word insert:
+        std::vector<int> output;
+        prefixes[i]->get_path_vec(output);
+        size_t prefix_length = output.size();
+        // remove language model weight:
+        if (ext_scorer != nullptr) {
+           // auto words = split_labels(output);
+           // approx_ctc = approx_ctc - path_length * ext_scorer->beta;
+           // approx_ctc -= (_lm->get_sent_log_prob(words)) * ext_scorer->alpha;
         }
 
-        log_probs_b_prev = log_probs_b_cur;
-        log_probs_nb_prev = log_probs_nb_cur;
-        std::vector<std::pair<std::string, log_prob_type> >
-                  prefix_vec_next(prefix_set_next.begin(),
-                                  prefix_set_next.end());
-        std::sort(prefix_vec_next.begin(),
-                  prefix_vec_next.end(),
-                  pair_comp_second_rev<std::string, log_prob_type>);
-        int num_prefixes_next = prefix_vec_next.size();
-        int k = beam_size<num_prefixes_next ? beam_size : num_prefixes_next;
-        prefix_set_prev = std::map<std::string, log_prob_type> (
-                                                   prefix_vec_next.begin(),
-                                                   prefix_vec_next.begin() + k
-                                                );
+        prefixes[i]->_approx_ctc = approx_ctc;
     }
 
-    // post processing
-    std::vector<std::pair<double, std::string> > beam_result;
-    for (std::map<std::string, log_prob_type>::iterator
-         it = prefix_set_prev.begin(); it != prefix_set_prev.end(); it++) {
-        if (it->second > -NUM_MAX && it->first.size() > 1) {
-            log_prob_type log_prob = it->second;
-            std::string sentence = it->first.substr(1);
-            // scoring the last word
-            if (ext_scorer != NULL && sentence[sentence.size()-1] != ' ') {
-                log_prob = log_prob + ext_scorer->get_score(sentence, true);
-            }
-            if (log_prob > -NUM_MAX) {
-                std::pair<double, std::string> cur_result(log_prob, sentence);
-                beam_result.push_back(cur_result);
-            }
+    // allow for the post processing
+    std::vector<PathTrie*> space_prefixes;
+    if (space_prefixes.empty()) {
+        for (size_t i = 0; i < beam_size && i< prefixes.size(); i++) {
+            space_prefixes.push_back(prefixes[i]);
         }
     }
-    // sort the result and return
-    std::sort(beam_result.begin(), beam_result.end(),
-              pair_comp_first_rev<double, std::string>);
-    return beam_result;
-}
+
+    std::sort(space_prefixes.begin(), space_prefixes.end(), prefix_compare);
+    std::vector<std::pair<double, std::string> > output_vecs;
+    for (size_t i = 0; i < beam_size && i < space_prefixes.size(); i++) {
+        std::vector<int> output;
+        space_prefixes[i]->get_path_vec(output);
+        // convert index to string
+        std::string output_str;
+        for (int j = 0; j < output.size(); j++) {
+            output_str += vocabulary[output[j]];
+        }
+        std::pair<double, std::string> output_pair(space_prefixes[i]->_score,
+                                                   output_str);
+        output_vecs.emplace_back(
+            output_pair
+        );
+    }
+
+    return output_vecs;
+ }
 
 
 std::vector<std::vector<std::pair<double, std::string>>>
@@ -250,8 +279,7 @@ std::vector<std::vector<std::pair<double, std::string>>>
                 int num_processes,
                 double cutoff_prob,
                 Scorer *ext_scorer
-                )
-{
+                ) {
     if (num_processes <= 0) {
         std::cout << "num_processes must be nonnegative!" << std::endl;
         exit(1);

deep_speech_2/deploy/decoder_utils.cpp

@@ -10,3 +10,73 @@ size_t get_utf8_str_len(const std::string& str) {
     }
     return str_len;
 }
+
+//-------------------------------------------------------
+//  Overriding less than operator for sorting
+//-------------------------------------------------------
+bool prefix_compare(const PathTrie* x,  const PathTrie* y) {
+    if (x->_score == y->_score) {
+        if (x->_character == y->_character) {
+            return false;
+        } else {
+            return (x->_character < y->_character);
+        }
+    } else {
+        return x->_score > y->_score;
+    }
+}  //---------- End path_compare ---------------------------
+
+// --------------------------------------------------------------
+// Adds word to fst without copying entire dictionary
+// --------------------------------------------------------------
+void add_word_to_fst(const std::vector<int>& word,
+                     fst::StdVectorFst* dictionary) {
+    if (dictionary->NumStates() == 0) {
+        fst::StdVectorFst::StateId start = dictionary->AddState();
+        assert(start == 0);
+        dictionary->SetStart(start);
+    }
+    fst::StdVectorFst::StateId src = dictionary->Start();
+    fst::StdVectorFst::StateId dst;
+    for (auto c : word) {
+        dst = dictionary->AddState();
+        dictionary->AddArc(src, fst::StdArc(c, c, 0, dst));
+        src = dst;
+    }
+    dictionary->SetFinal(dst, fst::StdArc::Weight::One());
+}  // ------------ End of add_word_to_fst -----------------------
+
+// ---------------------------------------------------------
+// Adds a word to the dictionary FST based on char_map
+// ---------------------------------------------------------
+bool addWordToDictionary(const std::string& word,
+                         const std::unordered_map<std::string, int>& char_map,
+                         bool add_space,
+                         int SPACE,
+                         fst::StdVectorFst* dictionary) {
+    /*
+    auto characters = UTF8_split(word);
+
+    std::vector<int> int_word;
+
+    for (auto& c : characters) {
+        if (c == " ") {
+            int_word.push_back(SPACE);
+        } else {
+            auto int_c = char_map.find(c);
+            if (int_c != char_map.end()) {
+                int_word.push_back(int_c->second);
+            } else {
+                return false;  // return without adding
+            }
+        }
+    }
+
+    if (add_space) {
+        int_word.push_back(SPACE);
+    }
+
+    add_word_to_fst(int_word, dictionary);
+    */
+    return true;
+}  // -------------- End of addWordToDictionary ------------

deep_speech_2/deploy/decoder_utils.h

@@ -2,6 +2,7 @@
 #define DECODER_UTILS_H_
 
 #include <utility>
+#include "path_trie.h"
 
 template <typename T1, typename T2>
 bool pair_comp_first_rev(const std::pair<T1, T2> &a, const std::pair<T1, T2> &b)
@@ -25,8 +26,21 @@ T log_sum_exp(const T &x, const T &y)
     return std::log(std::exp(x-xmax) + std::exp(y-xmax)) + xmax;
 }
 
+//-------------------------------------------------------
+//  Overriding less than operator for sorting
+//-------------------------------------------------------
+bool prefix_compare(const PathTrie* x,  const PathTrie* y);
+
 // Get length of utf8 encoding string
 // See: http://stackoverflow.com/a/4063229
 size_t get_utf8_str_len(const std::string& str);
 
+void add_word_to_fst(const std::vector<int>& word,
+                     fst::StdVectorFst* dictionary);
+
+bool addWordToDictionary(const std::string& word,
+                         const std::unordered_map<std::string, int>& char_map,
+                         bool add_space,
+                         int SPACE,
+                         fst::StdVectorFst* dictionary);
 #endif // DECODER_UTILS_H

deep_speech_2/deploy/path_trie.cpp

+#include <algorithm>
+#include <limits>
+#include <memory>
+#include <utility>
+#include <vector>
+
+#include "path_trie.h"
+#include "decoder_utils.h"
+
+PathTrie::PathTrie() {
+    float lowest = -1.0*std::numeric_limits<float>::max();
+    _log_prob_b_prev = lowest;
+    _log_prob_nb_prev = lowest;
+    _log_prob_b_cur = lowest;
+    _log_prob_nb_cur = lowest;
+    _score = lowest;
+
+    _ROOT = -1;
+    _character = _ROOT;
+    _exists = true;
+    _parent = nullptr;
+    _dictionary = nullptr;
+    _dictionary_state = 0;
+    _has_dictionary = false;
+    _matcher = nullptr;  // finds arcs in FST
+}
+
+PathTrie::~PathTrie() {
+    for (auto child : _children) {
+        delete child.second;
+    }
+}
+
+PathTrie* PathTrie::get_path_trie(int new_char, bool reset) {
+    auto child = _children.begin();
+    for (child = _children.begin(); child != _children.end(); ++child) {
+        if (child->first == new_char) {
+            break;
+        }
+    }
+    if ( child != _children.end() ) {
+        if (!child->second->_exists) {
+            child->second->_exists = true;
+            float lowest = -1.0*std::numeric_limits<float>::max();
+            child->second->_log_prob_b_prev = lowest;
+            child->second->_log_prob_nb_prev = lowest;
+            child->second->_log_prob_b_cur = lowest;
+            child->second->_log_prob_nb_cur = lowest;
+        }
+        return (child->second);
+    } else {
+        if (_has_dictionary) {
+            _matcher->SetState(_dictionary_state);
+            bool found = _matcher->Find(new_char);
+            if (!found) {
+                // Adding this character causes word outside dictionary
+                auto FSTZERO = fst::TropicalWeight::Zero();
+                auto final_weight = _dictionary->Final(_dictionary_state);
+                bool is_final = (final_weight != FSTZERO);
+                if (is_final && reset) {
+                    _dictionary_state = _dictionary->Start();
+                }
+                return nullptr;
+            } else {
+                PathTrie* new_path = new PathTrie;
+                new_path->_character = new_char;
+                new_path->_parent = this;
+                new_path->_dictionary = _dictionary;
+                new_path->_dictionary_state = _matcher->Value().nextstate;
+                new_path->_has_dictionary = true;
+                new_path->_matcher = _matcher;
+                _children.push_back(std::make_pair(new_char, new_path));
+                return new_path;
+            }
+        } else {
+            PathTrie* new_path = new PathTrie;
+            new_path->_character = new_char;
+            new_path->_parent = this;
+            _children.push_back(std::make_pair(new_char, new_path));
+            return new_path;
+        }
+    }
+}
+
+PathTrie* PathTrie::get_path_vec(std::vector<int>& output) {
+    return get_path_vec(output, _ROOT);
+}
+
+PathTrie* PathTrie::get_path_vec(std::vector<int>& output,
+        int stop,
+        size_t max_steps /*= std::numeric_limits<size_t>::max() */) {
+    if (_character == stop ||
+            _character == _ROOT ||
+            output.size() == max_steps) {
+        std::reverse(output.begin(), output.end());
+        return this;
+    } else {
+        output.push_back(_character);
+        return _parent->get_path_vec(output, stop, max_steps);
+    }
+}
+
+void PathTrie::iterate_to_vec(
+        std::vector<PathTrie*>& output) {
+    if (_exists) {
+        _log_prob_b_prev = _log_prob_b_cur;
+        _log_prob_nb_prev = _log_prob_nb_cur;
+
+        _log_prob_b_cur = -1.0 * std::numeric_limits<float>::max();
+        _log_prob_nb_cur = -1.0 * std::numeric_limits<float>::max();
+
+        _score = log_sum_exp(_log_prob_b_prev, _log_prob_nb_prev);
+        output.push_back(this);
+    }
+    for (auto child : _children) {
+        child.second->iterate_to_vec(output);
+    }
+}
+
+//-------------------------------------------------------
+//  Effectively removes node
+//-------------------------------------------------------
+void PathTrie::remove() {
+    _exists = false;
+
+    if (_children.size() == 0) {
+        auto child = _parent->_children.begin();
+        for (child = _parent->_children.begin();
+                child != _parent->_children.end(); ++child) {
+            if (child->first == _character) {
+                _parent->_children.erase(child);
+                break;
+            }
+        }
+
+        if ( _parent->_children.size() == 0 && !_parent->_exists ) {
+            _parent->remove();
+        }
+
+        delete this;
+    }
+}
+
+void PathTrie::set_dictionary(fst::StdVectorFst* dictionary) {
+    _dictionary = dictionary;
+    _dictionary_state = dictionary->Start();
+    _has_dictionary = true;
+}
+
+using FSTMATCH = fst::SortedMatcher<fst::StdVectorFst>;
+void PathTrie::set_matcher(std::shared_ptr<FSTMATCH> matcher) {
+    _matcher = matcher;
+}

deep_speech_2/deploy/path_trie.h

+#ifndef PATH_TRIE_H
+#define PATH_TRIE_H
+#pragma once
+#include <algorithm>
+#include <limits>
+#include <memory>
+#include <utility>
+#include <vector>
+#include <fst/fstlib.h>
+
+using FSTMATCH = fst::SortedMatcher<fst::StdVectorFst>;
+
+class PathTrie {
+public:
+    PathTrie();
+    ~PathTrie();
+
+    PathTrie* get_path_trie(int new_char, bool reset = true);
+
+    PathTrie* get_path_vec(std::vector<int> &output);
+
+    PathTrie* get_path_vec(std::vector<int>& output,
+                        int stop,
+                        size_t max_steps = std::numeric_limits<size_t>::max());
+
+    void iterate_to_vec(std::vector<PathTrie*> &output);
+
+    void set_dictionary(fst::StdVectorFst* dictionary);
+
+    void set_matcher(std::shared_ptr<FSTMATCH> matcher);
+
+    bool is_empty() {
+        return _ROOT == _character;
+    }
+
+    void remove();
+
+    float _log_prob_b_prev;
+    float _log_prob_nb_prev;
+    float _log_prob_b_cur;
+    float _log_prob_nb_cur;
+    float _score;
+    float _approx_ctc;
+
+
+    int  _ROOT;
+    int  _character;
+    bool _exists;
+
+    PathTrie *_parent;
+    std::vector<std::pair<int, PathTrie*> > _children;
+
+    fst::StdVectorFst* _dictionary;
+    fst::StdVectorFst::StateId _dictionary_state;
+    bool _has_dictionary;
+    std::shared_ptr<FSTMATCH> _matcher;
+};
+
+#endif // PATH_TRIE_H

deep_speech_2/deploy/scorer.cpp

@@ -175,3 +175,42 @@ double Scorer::get_score(std::string sentence, bool log) {
     }
     return final_score;
 }
+
+//--------------------------------------------------
+// Turn indices back into strings of chars
+//--------------------------------------------------
+std::vector<std::string> Scorer::make_ngram(PathTrie* prefix) {
+    /*
+    std::vector<std::string> ngram;
+    PathTrie* current_node = prefix;
+    PathTrie* new_node = nullptr;
+
+    for (int order = 0; order < _max_order; order++) {
+        std::vector<int> prefix_vec;
+
+        if (_is_character_based) {
+            new_node = current_node->get_path_vec(prefix_vec, ' ', 1);
+            current_node = new_node;
+        } else {
+            new_node = current_node->getPathVec(prefix_vec, ' ');
+            current_node = new_node->_parent;  // Skipping spaces
+        }
+
+        // reconstruct word
+        std::string word = vec2str(prefix_vec);
+        ngram.push_back(word);
+
+        if (new_node->_character == -1) {
+            // No more spaces, but still need order
+            for (int i = 0; i < max_order - order - 1; i++) {
+                ngram.push_back("<s>");
+            }
+            break;
+        }
+    }
+    std::reverse(ngram.begin(), ngram.end());
+    */
+    std::vector<std::string> ngram;
+    ngram.push_back("this");
+    return ngram;
+}  //---------------- End makeNgrams ------------------

deep_speech_2/deploy/scorer.h

@@ -4,10 +4,12 @@
 #include <string>
 #include <memory>
 #include <vector>
+#include <unordered_map>
 #include "lm/enumerate_vocab.hh"
 #include "lm/word_index.hh"
 #include "lm/virtual_interface.hh"
 #include "util/string_piece.hh"
+#include "path_trie.h"
 
 const double OOV_SCOER = -1000.0;
 const std::string START_TOKEN = "<s>";
@@ -49,18 +51,29 @@ public:
     void reset_params(float alpha, float beta);
     // get the final score
     double get_score(std::string, bool log=false);
+    // make ngram
+    std::vector<std::string> make_ngram(PathTrie* prefix);
     // expose to decoder
     double alpha;
     double beta;
+    // fst dictionary
+    void* dictionary;
 
 protected:
     void load_LM(const char* filename);
     double get_log_prob(const std::vector<std::string>& words);
 
 private:
+    void _init_char_list();
+    void _init_char_map();
+
     void* _language_model;
     bool _is_character_based;
     size_t _max_order;
+
+    std::vector<std::string> _char_list;
+    std::unordered_map<char, int> _char_map;
+
     std::vector<std::string> _vocabulary;
 };