PTTS / Hazm_correction.py
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import hazm
import typing
normalizer = hazm.Normalizer()
sent_tokenizer = hazm.SentenceTokenizer()
word_tokenizer = hazm.WordTokenizer()
tagger = hazm.POSTagger(
model=str("gyroing/PersianTextCorrection_Hazm/pos_tagger.model")
)
def preprocess_text(text: str) -> typing.List[typing.List[str]]:
"""Split/normalize text into sentences/words with hazm"""
text = normalizer.normalize(text)
processed_sentences = []
for sentence in sent_tokenizer.tokenize(text):
words = word_tokenizer.tokenize(sentence)
processed_words = fix_words(words)
processed_sentences.append(" ".join(processed_words))
return " ".join(processed_sentences)
def fix_words(words: typing.List[str]) -> typing.List[str]:
fixed_words = []
for word, pos in tagger.tag(words):
if pos[-1] == "Z":
if word[-1] != "ِ":
if (word[-1] == "ه") and (word[-2] != "ا"):
word += "‌ی"
word += "ِ"
fixed_words.append(word)
return fixed_words