/**
* @name chop_word_main
*
* Classify the blobs in this word and permute the results. Find the
* worst blob in the word and chop it up. Continue this process until
* a good answer has been found or all the blobs have been chopped up
* enough. The results are returned in the WERD_RES.
*/
void Wordrec::chop_word_main(WERD_RES *word) {
int num_blobs = word->chopped_word->NumBlobs();
if (word->ratings == NULL) {
word->ratings = new MATRIX(num_blobs, wordrec_max_join_chunks);
}
if (word->ratings->get(0, 0) == NULL) {
// Run initial classification.
for (int b = 0; b < num_blobs; ++b) {
BLOB_CHOICE_LIST* choices = classify_piece(word->seam_array, b, b,
"Initial:", word->chopped_word,
word->blamer_bundle);
word->ratings->put(b, b, choices);
}
} else {
// Blobs have been pre-classified. Set matrix cell for all blob choices
for (int col = 0; col < word->ratings->dimension(); ++col) {
for (int row = col; row < word->ratings->dimension() &&
row < col + word->ratings->bandwidth(); ++row) {
BLOB_CHOICE_LIST* choices = word->ratings->get(col, row);
if (choices != NULL) {
BLOB_CHOICE_IT bc_it(choices);
for (bc_it.mark_cycle_pt(); !bc_it.cycled_list(); bc_it.forward()) {
bc_it.data()->set_matrix_cell(col, row);
}
}
}
}
}
// Run Segmentation Search.
BestChoiceBundle best_choice_bundle(word->ratings->dimension());
SegSearch(word, &best_choice_bundle, word->blamer_bundle);
if (word->best_choice == NULL) {
// SegSearch found no valid paths, so just use the leading diagonal.
word->FakeWordFromRatings();
}
word->RebuildBestState();
// If we finished without a hyphen at the end of the word, let the next word
// be found in the dictionary.
if (word->word->flag(W_EOL) &&
!getDict().has_hyphen_end(*word->best_choice)) {
getDict().reset_hyphen_vars(true);
}
if (word->blamer_bundle != NULL && this->fill_lattice_ != NULL) {
CallFillLattice(*word->ratings, word->best_choices,
*word->uch_set, word->blamer_bundle);
}
if (wordrec_debug_level > 0) {
tprintf("Final Ratings Matrix:\n");
word->ratings->print(getDict().getUnicharset());
}
word->FilterWordChoices(getDict().stopper_debug_level);
}
MATRIX *Wordrec::word_associator(WERD_RES *word,
STATE *state,
BLOB_CHOICE_LIST_VECTOR *best_char_choices,
DANGERR *fixpt,
STATE *best_state) {
CHUNKS_RECORD chunks_record;
BLOB_WEIGHTS blob_weights;
int x;
int num_chunks;
BLOB_CHOICE_IT blob_choice_it;
num_chunks = array_count(word->seam_array) + 1;
TBLOB* blobs = word->chopped_word->blobs;
chunks_record.chunks = blobs;
chunks_record.splits = word->seam_array;
chunks_record.ratings = record_piece_ratings (blobs);
chunks_record.char_widths = blobs_widths (blobs);
chunks_record.chunk_widths = blobs_widths (blobs);
/* Save chunk weights */
for (x = 0; x < num_chunks; x++) {
BLOB_CHOICE_LIST* choices = get_piece_rating(chunks_record.ratings,
blobs, word->seam_array, x, x);
blob_choice_it.set_to_list(choices);
//This is done by Jetsoft. Divide by zero is possible.
if (blob_choice_it.data()->certainty() == 0) {
blob_weights[x]=0;
} else {
blob_weights[x] =
-(inT16) (10 * blob_choice_it.data()->rating() /
blob_choice_it.data()->certainty());
}
}
chunks_record.weights = blob_weights;
if (chop_debug)
chunks_record.ratings->print(getDict().getUnicharset());
if (enable_new_segsearch) {
SegSearch(&chunks_record, word->best_choice,
best_char_choices, word->raw_choice, state);
} else {
best_first_search(&chunks_record, best_char_choices, word,
state, fixpt, best_state);
}
free_widths (chunks_record.chunk_widths);
free_widths (chunks_record.char_widths);
return chunks_record.ratings;
}
void Wordrec::DoSegSearch(WERD_RES* word_res) {
BestChoiceBundle best_choice_bundle(word_res->ratings->dimension());
// Run Segmentation Search.
SegSearch(word_res, &best_choice_bundle, NULL);
}
