89 lines
2.6 KiB
Python
89 lines
2.6 KiB
Python
import re
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import pandas as pd
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import math
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from functools import reduce
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import argparse
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import os
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import sqlite3
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def genmod():
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corpus_path = "./corpus/"
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df_list = []
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for file in os.listdir(corpus_path):
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if file.endswith(".csv"):
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df = pd.read_csv(corpus_path+file, header=0, names=['hanji', 'lomaji'])
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df_list.append(df)
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df = pd.concat(df_list)
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df['lomaji'] = df['lomaji'].str.lower()
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new_data = []
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for index, row in df.iterrows():
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hanji = list(filter(lambda x : re.match("[^、（）；：，。！？「」『』]", x), list(row['hanji'])))
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tl = re.split(r'(:?[!?;,.\"\'\(\):]|[-]+|\s+)', row['lomaji'])
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tl2 = list(filter(lambda x : re.match(r"([^\(\)^!:?; \'\",.\-\u3000])", x), tl))
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new_data.append((hanji, tl2))
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if (len(hanji) != len(tl2)):
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raise ValueError(f"length of hanji {hanji} is different from romaji {tl2}.")
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model_filename = "model.db"
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try:
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os.remove(model_filename)
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except OSError:
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pass
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con = sqlite3.connect(model_filename)
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cur = con.cursor()
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cur.execute("CREATE TABLE pronounce(hanji, lomaji, freq)")
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char_to_pronounce = {}
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for i in new_data:
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hanji = i[0]
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lomaji = i[1]
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for j in range(len(i[0])):
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if not hanji[j] in char_to_pronounce:
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char_to_pronounce[hanji[j]] = {lomaji[j] : 1}
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elif not lomaji[j] in char_to_pronounce[hanji[j]]:
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char_to_pronounce[hanji[j]][lomaji[j]] = 1
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else:
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char_to_pronounce[hanji[j]][lomaji[j]] += 1
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print(char_to_pronounce)
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for i in char_to_pronounce.keys():
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hanji = char_to_pronounce[i]
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for j in hanji.keys():
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cur.execute("INSERT INTO pronounce VALUES(?, ?, ?)", (i,j, hanji[j]))
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#con.commit()
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con.commit()
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con.close()
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def convert(sentence):
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pass
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parser = argparse.ArgumentParser()
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parser.add_argument('--genmod', help='generate the model', action='store_true',
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required=False,)
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parser.add_argument('sentence', metavar='SENTENCE', nargs='?',
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help='the sentence to be converted')
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parser.add_argument('--form', metavar='FORM', choices=["poj", "tl"], nargs=1,
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default=['poj'],
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help='the orthography to be used (poj or tl). Default is poj.')
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args = parser.parse_args()
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print(args)
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if args.genmod == True:
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genmod()
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elif args.sentence != None:
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if args.form == ['poj']:
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sentence = poj_to_tl(args.sentence)
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print(convert(sentence))
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else:
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print(convert(args.sentence))
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else:
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parser.print_help()
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