ukrainian-stt / deepspeech /extract_text_corpus.py
Yurii Paniv
Reorganize repo
1f211a9
# this script is used for importing random texts from folder and converting it for scorer
import os
import nltk
import re
nltk.download("punkt")
FOLDER = "../data/текст/"
OUT_FILE = "../data/texts.txt"
text_file = open(OUT_FILE, mode="a")
tokenizer = nltk.SpaceTokenizer()
paranthesis_regex = re.compile(r'\(.*\)')
allowed_chars = ["а", "б", "в", "г", "ґ", "д", "е", "є", "ж", "з", "и", "і", "ї", "й", "к", "л",
"м", "н", "о", "п", "р", "с", "т", "у", "ф", "х", "ц", "ч", "ш", "щ", "ь", "ю", "я", "-", "’"]
for subdir, dirs, files in os.walk(FOLDER):
for file in files:
file_path = os.path.join(subdir, file)
print(file_path)
input_file = open(file_path)
try:
cleaned_text = input_file.read()
except:
input_file.close()
input_file = open(file_path, encoding="cp1251")
cleaned_text = input_file.read()
cleaned_text = cleaned_text.lower()
cleaned_text = cleaned_text.replace("'", "’")
cleaned_text = paranthesis_regex.sub('', cleaned_text)
cleaned_text = cleaned_text.strip()
cleaned_text = cleaned_text.split(".")
out_text = []
for text in cleaned_text:
text = text.strip()
words = tokenizer.tokenize(text)
words = [i for i in words if not i.isdigit()]
new_words = []
for word in words:
include = True
for letter in word:
if word.startswith("-"):
word = word[1:]
if letter not in allowed_chars:
include = False
if include:
new_words.append(word)
words = new_words
if all([len(i) <= 1 for i in words]):
continue
if len(words) == 0:
continue
out_text.append(
" ".join(words))
cleaned_text = "\n".join(out_text)
if cleaned_text == "":
continue
text_file.write(cleaned_text + "\n")
input_file.close()
text_file.close()