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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
from typing import List
from .char_convert import tranditional_to_simplified
from .chronology import RE_DATE
from .chronology import RE_DATE2
from .chronology import RE_TIME
from .chronology import RE_TIME_RANGE
from .chronology import replace_date
from .chronology import replace_date2
from .chronology import replace_time
from .constants import F2H_ASCII_LETTERS
from .constants import F2H_DIGITS
from .constants import F2H_SPACE
from .num import RE_DECIMAL_NUM
from .num import RE_DEFAULT_NUM
from .num import RE_FRAC
from .num import RE_INTEGER
from .num import RE_NUMBER
from .num import RE_PERCENTAGE
from .num import RE_POSITIVE_QUANTIFIERS
from .num import RE_RANGE
from .num import RE_TO_RANGE
from .num import RE_ASMD
from .num import RE_POWER
from .num import replace_default_num
from .num import replace_frac
from .num import replace_negative_num
from .num import replace_number
from .num import replace_percentage
from .num import replace_positive_quantifier
from .num import replace_range
from .num import replace_to_range
from .num import replace_asmd
from .num import replace_power
from .phonecode import RE_MOBILE_PHONE
from .phonecode import RE_NATIONAL_UNIFORM_NUMBER
from .phonecode import RE_TELEPHONE
from .phonecode import replace_mobile
from .phonecode import replace_phone
from .quantifier import RE_TEMPERATURE
from .quantifier import replace_measure
from .quantifier import replace_temperature
class TextNormalizer():
def __init__(self):
self.SENTENCE_SPLITOR = re.compile(r'([：、，；。？！,;?!][”’]?)')
def _split(self, text: str, lang="zh") -> List[str]:
"""Split long text into sentences with sentence-splitting punctuations.
Args:
text (str): The input text.
Returns:
List[str]: Sentences.
"""
# Only for pure Chinese here
if lang == "zh":
text = text.replace(" ", "")
# 过滤掉特殊字符
text = re.sub(r'[——《》【】<>{}()（）#&@“”^_|\\]', '', text)
text = self.SENTENCE_SPLITOR.sub(r'\1\n', text)
text = text.strip()
sentences = [sentence.strip() for sentence in re.split(r'\n+', text)]
return sentences
def _post_replace(self, sentence: str) -> str:
sentence = sentence.replace('/', '每')
# sentence = sentence.replace('~', '至')
# sentence = sentence.replace('～', '至')
sentence = sentence.replace('①', '一')
sentence = sentence.replace('②', '二')
sentence = sentence.replace('③', '三')
sentence = sentence.replace('④', '四')
sentence = sentence.replace('⑤', '五')
sentence = sentence.replace('⑥', '六')
sentence = sentence.replace('⑦', '七')
sentence = sentence.replace('⑧', '八')
sentence = sentence.replace('⑨', '九')
sentence = sentence.replace('⑩', '十')
sentence = sentence.replace('α', '阿尔法')
sentence = sentence.replace('β', '贝塔')
sentence = sentence.replace('γ', '伽玛').replace('Γ', '伽玛')
sentence = sentence.replace('δ', '德尔塔').replace('Δ', '德尔塔')
sentence = sentence.replace('ε', '艾普西龙')
sentence = sentence.replace('ζ', '捷塔')
sentence = sentence.replace('η', '依塔')
sentence = sentence.replace('θ', '西塔').replace('Θ', '西塔')
sentence = sentence.replace('ι', '艾欧塔')
sentence = sentence.replace('κ', '喀帕')
sentence = sentence.replace('λ', '拉姆达').replace('Λ', '拉姆达')
sentence = sentence.replace('μ', '缪')
sentence = sentence.replace('ν', '拗')
sentence = sentence.replace('ξ', '克西').replace('Ξ', '克西')
sentence = sentence.replace('ο', '欧米克伦')
sentence = sentence.replace('π', '派').replace('Π', '派')
sentence = sentence.replace('ρ', '肉')
sentence = sentence.replace('ς', '西格玛').replace('Σ', '西格玛').replace(
'σ', '西格玛')
sentence = sentence.replace('τ', '套')
sentence = sentence.replace('υ', '宇普西龙')
sentence = sentence.replace('φ', '服艾').replace('Φ', '服艾')
sentence = sentence.replace('χ', '器')
sentence = sentence.replace('ψ', '普赛').replace('Ψ', '普赛')
sentence = sentence.replace('ω', '欧米伽').replace('Ω', '欧米伽')
# 兜底数学运算，顺便兼容懒人用语
sentence = sentence.replace('+', '加')
sentence = sentence.replace('-', '减')
sentence = sentence.replace('×', '乘')
sentence = sentence.replace('÷', '除')
sentence = sentence.replace('=', '等')
# re filter special characters, have one more character "-" than line 68
sentence = re.sub(r'[-——《》【】<=>{}()（）#&@“”^_|\\]', '', sentence)
return sentence
def normalize_sentence(self, sentence: str) -> str:
# basic character conversions
sentence = tranditional_to_simplified(sentence)
sentence = sentence.translate(F2H_ASCII_LETTERS).translate(
F2H_DIGITS).translate(F2H_SPACE)
# number related NSW verbalization
sentence = RE_DATE.sub(replace_date, sentence)
sentence = RE_DATE2.sub(replace_date2, sentence)
# range first
sentence = RE_TIME_RANGE.sub(replace_time, sentence)
sentence = RE_TIME.sub(replace_time, sentence)
# 处理~波浪号作为至的替换
sentence = RE_TO_RANGE.sub(replace_to_range, sentence)
sentence = RE_TEMPERATURE.sub(replace_temperature, sentence)
sentence = replace_measure(sentence)
# 处理数学运算
while RE_ASMD.search(sentence):
sentence = RE_ASMD.sub(replace_asmd, sentence)
sentence = RE_POWER.sub(replace_power, sentence)
sentence = RE_FRAC.sub(replace_frac, sentence)
sentence = RE_PERCENTAGE.sub(replace_percentage, sentence)
sentence = RE_MOBILE_PHONE.sub(replace_mobile, sentence)
sentence = RE_TELEPHONE.sub(replace_phone, sentence)
sentence = RE_NATIONAL_UNIFORM_NUMBER.sub(replace_phone, sentence)
sentence = RE_RANGE.sub(replace_range, sentence)
sentence = RE_INTEGER.sub(replace_negative_num, sentence)
sentence = RE_DECIMAL_NUM.sub(replace_number, sentence)
sentence = RE_POSITIVE_QUANTIFIERS.sub(replace_positive_quantifier,
sentence)
sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence)
sentence = RE_NUMBER.sub(replace_number, sentence)
sentence = self._post_replace(sentence)
return sentence
def normalize(self, text: str) -> List[str]:
sentences = self._split(text)
sentences = [self.normalize_sentence(sent) for sent in sentences]
return sentences
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