def transliterate_bilstm_top3(sentence):
"""
Transliterate signs using biLSTM
:param sentence: signs to be transliterated
:return: 3 top transliterations of the sentence with their scores
"""
sentence = sanitize(sentence)
model, predictor, sign_to_id, id_to_tran, test_texts = load_object_from_file(bilstm_path)
tag_logits = predictor.predict(sentence_to_allen_format(sentence, sign_to_id, True))['tag_logits']
prediction1, prediction2, prediction3, score1, score2, score3 = logits_to_trans(tag_logits, model, id_to_tran)
return list_to_tran(prediction1), list_to_tran(prediction2), list_to_tran(prediction3)
def transliterate_bilstm(sentence):
"""
Transliterate signs using biLSTM
:param sentence: signs to be transliterated
:return: transliteration of the sentence
"""
sentence = sanitize(sentence)
model, predictor, sign_to_id, id_to_tran, test_texts = load_object_from_file(bilstm_path)
tag_logits = predictor.predict(sentence_to_allen_format(sentence, sign_to_id, True))['tag_logits']
biLSTM_predicted_tags, _, _, _, _, _ = logits_to_trans(tag_logits, model, id_to_tran)
return list_to_tran(biLSTM_predicted_tags)
def transliterate_memm(sentence):
"""
Transliterate signs using MEMM
:param sentence: signs to be transliterated
:return: transliteration of the sentence
"""
sentence = sanitize(sentence)
logreg, vec, idx_to_tag_dict, test_texts = load_object_from_file(memm_path)
MEMM_predicted_tags = memm_greedy(sentence_to_HMM_format(sentence), logreg, vec, idx_to_tag_dict)
return list_to_tran(MEMM_predicted_tags)
def transliterate_memm(sentence):
"""
Transliterate signs using MEMM
:param sentence: signs to be transliterated
:return: transliteration of the sentence
"""
sentences = [sanitize(line) for line in sentence.splitlines() if len(sanitize(line)) > 0]
logreg, vec, idx_to_tag_dict, test_texts = load_object_from_file(memm_path)
MEMM_predicted_tags_list = [memm_greedy(sentence_to_HMM_format(s), logreg, vec, idx_to_tag_dict) for s in sentences]
tran_list = [list_to_tran(MEMM_predicted_tags) for MEMM_predicted_tags in MEMM_predicted_tags_list]
return ''.join(tran_list)
def transliterate_hmm(sentence):
"""
Transliterate signs using HMM
:param sentence: signs to be transliterated
:return: transliteration of the sentence
"""
sentence = sanitize(sentence)
most_common_tag, possible_tags, q, e, S, total_tokens, q_bi_counts, q_uni_counts, lambda1, lambda2, test_texts = \
load_object_from_file(hmm_path)
HMM_predicted_tags = hmm_viterbi(sentence_to_HMM_format(sentence), total_tokens, q_bi_counts, q_uni_counts, q, e,
S, most_common_tag, possible_tags, lambda1, lambda2)
return list_to_tran(HMM_predicted_tags)
def transliterate_hmm(sentence):
"""
Transliterate signs using HMM
:param sentence: signs to be transliterated
:return: transliteration of the sentence
"""
sentences = [sanitize(line) for line in sentence.splitlines() if len(sanitize(line)) > 0]
most_common_tag, possible_tags, q, e, S, total_tokens, q_bi_counts, q_uni_counts, lambda1, lambda2, test_texts = \
load_object_from_file(hmm_path)
HMM_predicted_tags_list = [hmm_viterbi(sentence_to_HMM_format(s), total_tokens, q_bi_counts, q_uni_counts, q, e,
S, most_common_tag, possible_tags, lambda1, lambda2) for s in sentences]
tran_list = [list_to_tran(HMM_predicted_tags) for HMM_predicted_tags in HMM_predicted_tags_list]
return ''.join(tran_list)