Hui Zhang
3 years ago
committed by
GitHub
commit
65850e4d00
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# Regular expression based text normalization for Chinese
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For simplicity and ease of implementation, text normalization is basically done by rules and dictionaries. Jere's an example.
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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from text_processing import normalization
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parser = argparse.ArgumentParser(
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description="Normalize text in Chinese with some rules.")
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parser.add_argument("input", type=str, help="the input sentences")
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parser.add_argument("output", type=str, help="path to save the output file.")
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args = parser.parse_args()
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with open(args.input, 'rt') as fin:
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with open(args.output, 'wt') as fout:
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for sent in fin:
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sent = normalization.normalize_sentence(sent.strip())
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fout.write(sent)
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fout.write('\n')
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export MAIN_ROOT=${PWD}/../../
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export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
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export LC_ALL=C
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# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
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export PYTHONIOENCODING=UTF-8
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export PYTHONPATH=${MAIN_ROOT}:${MAIN_ROOT}/third_party:${PYTHONPATH}#
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#!/usr/bin/env bash
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source path.sh
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stage=-1
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stop_stage=100
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exp_dir=exp
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data_dir=data
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filename="sentences.txt"
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source ${MAIN_ROOT}/utils/parse_options.sh || exit -1
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mkdir -p ${exp_dir}
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if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
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echo "stage 1: Processing "
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python3 local/test_normalization.py ${data_dir}/${filename} ${exp_dir}/normalized.txt
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if [ -f "${exp_dir}/normalized.txt" ]; then
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echo "Normalized text save at ${exp_dir}/normalized.txt"
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fi
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# TODO(chenfeiyu): compute edit distance against ground-truth
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fi
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echo "done"
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exit 0
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from .sentence_split import split
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from .num import RE_NUMBER, RE_FRAC, RE_PERCENTAGE, RE_RANGE, RE_INTEGER, RE_DEFAULT_NUM
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from .num import replace_number, replace_frac, replace_percentage, replace_range, replace_default_num
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from .chronology import RE_TIME, RE_DATE, RE_DATE2
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from .chronology import replace_time, replace_date, replace_date2
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from .quantifier import RE_TEMPERATURE
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from .quantifier import replace_temperature
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from .phone import RE_MOBILE_PHONE, RE_TELEPHONE, replace_phone
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from .char_convert import tranditional_to_simplified
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from .constants import F2H_ASCII_LETTERS, F2H_DIGITS, F2H_SPACE
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def normalize_sentence(sentence):
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# basic character conversions
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sentence = tranditional_to_simplified(sentence)
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sentence = sentence.translate(F2H_ASCII_LETTERS).translate(
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F2H_DIGITS).translate(F2H_SPACE)
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# number related NSW verbalization
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sentence = RE_DATE.sub(replace_date, sentence)
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sentence = RE_DATE2.sub(replace_date2, sentence)
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sentence = RE_TIME.sub(replace_time, sentence)
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sentence = RE_TEMPERATURE.sub(replace_temperature, sentence)
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sentence = RE_RANGE.sub(replace_range, sentence)
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sentence = RE_FRAC.sub(replace_frac, sentence)
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sentence = RE_PERCENTAGE.sub(replace_percentage, sentence)
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sentence = RE_MOBILE_PHONE.sub(replace_phone, sentence)
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sentence = RE_TELEPHONE.sub(replace_phone, sentence)
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sentence = RE_DEFAULT_NUM.sub(replace_default_num, sentence)
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sentence = RE_NUMBER.sub(replace_number, sentence)
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return sentence
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def normalize(text):
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sentences = split(text)
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sentences = [normalize_sentence(sent) for sent in sentences]
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return sentences
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"""Traditional and simplified Chinese conversion with
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`opencc <https://github.com/BYVoid/OpenCC>`_.
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"""
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import opencc
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_t2s_converter = opencc.OpenCC("t2s.json")
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_s2t_converter = opencc.OpenCC('s2t.json')
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def tranditional_to_simplified(text: str) -> str:
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return _t2s_converter.convert(text)
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def simplified_to_traditional(text: str) -> str:
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return _s2t_converter.convert(text)
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import re
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from .num import verbalize_cardinal, verbalize_digit, num2str, DIGITS
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def _time_num2str(num_string: str) -> str:
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"""A special case for verbalizing number in time."""
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result = num2str(num_string.lstrip('0'))
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if num_string.startswith('0'):
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result = DIGITS['0'] + result
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return result
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# 时刻表达式
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RE_TIME = re.compile(
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r'([0-1]?[0-9]|2[0-3])'
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r':([0-5][0-9])'
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r'(:([0-5][0-9]))?'
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)
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def replace_time(match: re.Match) -> str:
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hour = match.group(1)
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minute = match.group(2)
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second = match.group(4)
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result = f"{num2str(hour)}点"
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if minute.lstrip('0'):
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result += f"{_time_num2str(minute)}分"
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if second and second.lstrip('0'):
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result += f"{_time_num2str(second)}秒"
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return result
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RE_DATE = re.compile(
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r'(\d{4}|\d{2})年'
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r'((0?[1-9]|1[0-2])月)?'
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r'(((0?[1-9])|((1|2)[0-9])|30|31)([日号]))?'
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)
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def replace_date(match: re.Match) -> str:
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year = match.group(1)
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month = match.group(3)
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day = match.group(5)
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result = ""
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if year:
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result += f"{verbalize_digit(year)}年"
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if month:
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result += f"{verbalize_cardinal(month)}月"
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if day:
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result += f"{verbalize_cardinal(day)}{match.group(9)}"
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return result
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# 用 / 或者 - 分隔的 YY/MM/DD 或者 YY-MM-DD 日期
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RE_DATE2 = re.compile(
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r'(\d{4})([- /.])(0[1-9]|1[012])\2(0[1-9]|[12][0-9]|3[01])'
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)
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def replace_date2(match: re.Match) -> str:
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year = match.group(1)
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month = match.group(3)
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day = match.group(4)
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result = ""
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if year:
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result += f"{verbalize_digit(year)}年"
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if month:
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result += f"{verbalize_cardinal(month)}月"
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if day:
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result += f"{verbalize_cardinal(day)}日"
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return result
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"""
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Rules to verbalize numbers into Chinese characters.
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https://zh.wikipedia.org/wiki/中文数字#現代中文
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"""
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import re
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from typing import List
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from collections import OrderedDict
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DIGITS = {str(i): tran for i, tran in enumerate('零一二三四五六七八九')}
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UNITS = OrderedDict({
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1: '十',
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2: '百',
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3: '千',
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4: '万',
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8: '亿',
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})
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# 分数表达式
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RE_FRAC = re.compile(r'(-?)(\d+)/(\d+)')
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def replace_frac(match: re.Match) -> str:
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sign = match.group(1)
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nominator = match.group(2)
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denominator = match.group(3)
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sign: str = "负" if sign else ""
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nominator: str = num2str(nominator)
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denominator: str = num2str(denominator)
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result = f"{sign}{denominator}分之{nominator}"
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return result
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# 百分数表达式
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RE_PERCENTAGE = re.compile(r'(-?)(\d+(\.\d+)?)%')
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def replace_percentage(match: re.Match) -> str:
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sign = match.group(1)
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percent = match.group(2)
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sign: str = "负" if sign else ""
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percent: str = num2str(percent)
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result = f"{sign}百分之{percent}"
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return result
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# 整数表达式
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# 带负号或者不带负号的整数 12, -10
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RE_INTEGER = re.compile(
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r'(-?)'
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r'(\d+)'
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)
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# 编号-无符号整形
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# 00078
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RE_DEFAULT_NUM = re.compile(r'\d{4}\d*')
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def replace_default_num(match: re.Match):
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number = match.group(0)
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return verbalize_digit(number)
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# 数字表达式
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# 1. 整数: -10, 10;
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# 2. 浮点数: 10.2, -0.3
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# 3. 不带符号和整数部分的纯浮点数: .22, .38
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RE_NUMBER = re.compile(
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r'(-?)((\d+)(\.\d+)?)'
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r'|(\.(\d+))'
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)
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def replace_number(match: re.Match) -> str:
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sign = match.group(1)
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number = match.group(2)
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pure_decimal = match.group(5)
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if pure_decimal:
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result = num2str(pure_decimal)
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else:
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sign: str = "负" if sign else ""
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number: str = num2str(number)
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result = f"{sign}{number}"
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return result
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# 范围表达式
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# 12-23, 12~23
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RE_RANGE = re.compile(
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r'(\d+)[-~](\d+)'
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)
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def replace_range(match: re.Match) -> str:
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first, second = match.group(1), match.group(2)
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first: str = num2str(first)
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second: str = num2str(second)
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result = f"{first}到{second}"
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return result
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def _get_value(value_string: str, use_zero: bool=True) -> List[str]:
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stripped = value_string.lstrip('0')
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if len(stripped) == 0:
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return []
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elif len(stripped) == 1:
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if use_zero and len(stripped) < len(value_string):
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return [DIGITS['0'], DIGITS[stripped]]
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else:
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return [DIGITS[stripped]]
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else:
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largest_unit = next(power for power in reversed(UNITS.keys()) if power < len(stripped))
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first_part = value_string[:-largest_unit]
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second_part = value_string[-largest_unit:]
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return _get_value(first_part) + [UNITS[largest_unit]] + _get_value(second_part)
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def verbalize_cardinal(value_string: str) -> str:
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if not value_string:
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return ''
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# 000 -> '零' , 0 -> '零'
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value_string = value_string.lstrip('0')
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if len(value_string) == 0:
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return DIGITS['0']
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result_symbols = _get_value(value_string)
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# verbalized number starting with '一十*' is abbreviated as `十*`
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if len(result_symbols) >= 2 and result_symbols[0] == DIGITS['1'] and result_symbols[1] == UNITS[1]:
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result_symbols = result_symbols[1:]
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return ''.join(result_symbols)
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def verbalize_digit(value_string: str, alt_one=False) -> str:
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result_symbols = [DIGITS[digit] for digit in value_string]
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result = ''.join(result_symbols)
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if alt_one:
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result.replace("一", "幺")
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return result
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def num2str(value_string: str) -> str:
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integer_decimal = value_string.split('.')
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if len(integer_decimal) == 1:
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integer = integer_decimal[0]
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decimal = ''
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elif len(integer_decimal) == 2:
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integer, decimal = integer_decimal
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else:
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raise ValueError(f"The value string: '${value_string}' has more than one point in it.")
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result = verbalize_cardinal(integer)
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decimal = decimal.rstrip('0')
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if decimal:
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# '.22' is verbalized as '点二二'
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# '3.20' is verbalized as '三点二
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result += '点' + verbalize_digit(decimal)
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return result
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import re
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from .num import num2str
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# 温度表达式，温度会影响负号的读法
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# -3°C 零下三度
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RE_TEMPERATURE = re.compile(
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r'(-?)(\d+(\.\d+)?)(°C|℃|度|摄氏度)'
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)
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def replace_temperature(match: re.Match) -> str:
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sign = match.group(1)
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temperature = match.group(2)
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unit = match.group(3)
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sign: str = "零下" if sign else ""
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temperature: str = num2str(temperature)
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unit: str = "摄氏度" if unit == "摄氏度" else "度"
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result = f"{sign}{temperature}{unit}"
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return result
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import re
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from typing import List
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SENTENCE_SPLITOR = re.compile(r'([。！？][”’]?)')
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def split(text: str) -> List[str]:
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"""Split long text into sentences with sentence-splitting punctuations.
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Parameters
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----------
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text : str
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The input text.
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Returns
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-------
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List[str]
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Sentences.
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"""
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text = SENTENCE_SPLITOR.sub(r'\1\n', text)
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text = text.strip()
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sentences = [sentence.strip() for sentence in re.split(r'\n+', text)]
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return sentences
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