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v0.5.9

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修复了记忆刷屏 加入了又新又好错别字生成器 增加了记忆过滤
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SengokuCola
2025-03-07 00:09:36 +08:00
parent 21d1a69b6e
commit 8ef00ee571
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src/plugins/utils/typo_generator.py Normal file
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"""
错别字生成器 - 基于拼音和字频的中文错别字生成工具
"""
from pypinyin import pinyin, Style
from collections import defaultdict
import json
import os
import jieba
from pathlib import Path
import random
import math
import time
class ChineseTypoGenerator:
def __init__(self,
error_rate=0.3,
min_freq=5,
tone_error_rate=0.2,
word_replace_rate=0.3,
max_freq_diff=200):
"""
初始化错别字生成器
参数:
error_rate: 单字替换概率
min_freq: 最小字频阈值
tone_error_rate: 声调错误概率
word_replace_rate: 整词替换概率
max_freq_diff: 最大允许的频率差异
"""
self.error_rate = error_rate
self.min_freq = min_freq
self.tone_error_rate = tone_error_rate
self.word_replace_rate = word_replace_rate
self.max_freq_diff = max_freq_diff
# 加载数据
print("正在加载汉字数据库，请稍候...")
self.pinyin_dict = self._create_pinyin_dict()
self.char_frequency = self._load_or_create_char_frequency()
def _load_or_create_char_frequency(self):
"""
加载或创建汉字频率字典
"""
cache_file = Path("char_frequency.json")
# 如果缓存文件存在，直接加载
if cache_file.exists():
with open(cache_file, 'r', encoding='utf-8') as f:
return json.load(f)
# 使用内置的词频文件
char_freq = defaultdict(int)
dict_path = os.path.join(os.path.dirname(jieba.__file__), 'dict.txt')
# 读取jieba的词典文件
with open(dict_path, 'r', encoding='utf-8') as f:
for line in f:
word, freq = line.strip().split()[:2]
# 对词中的每个字进行频率累加
for char in word:
if self._is_chinese_char(char):
char_freq[char] += int(freq)
# 归一化频率值
max_freq = max(char_freq.values())
normalized_freq = {char: freq/max_freq * 1000 for char, freq in char_freq.items()}
# 保存到缓存文件
with open(cache_file, 'w', encoding='utf-8') as f:
json.dump(normalized_freq, f, ensure_ascii=False, indent=2)
return normalized_freq
def _create_pinyin_dict(self):
"""
创建拼音到汉字的映射字典
"""
# 常用汉字范围
chars = [chr(i) for i in range(0x4e00, 0x9fff)]
pinyin_dict = defaultdict(list)
# 为每个汉字建立拼音映射
for char in chars:
try:
py = pinyin(char, style=Style.TONE3)[0][0]
pinyin_dict[py].append(char)
except Exception:
continue
return pinyin_dict
def _is_chinese_char(self, char):
"""
判断是否为汉字
"""
try:
return '\u4e00' <= char <= '\u9fff'
except:
return False
def _get_pinyin(self, sentence):
"""
将中文句子拆分成单个汉字并获取其拼音
"""
# 将句子拆分成单个字符
characters = list(sentence)
# 获取每个字符的拼音
result = []
for char in characters:
# 跳过空格和非汉字字符
if char.isspace() or not self._is_chinese_char(char):
continue
# 获取拼音（数字声调）
py = pinyin(char, style=Style.TONE3)[0][0]
result.append((char, py))
return result
def _get_similar_tone_pinyin(self, py):
"""
获取相似声调的拼音
"""
# 检查拼音是否为空或无效
if not py or len(py) < 1:
return py
# 如果最后一个字符不是数字，说明可能是轻声或其他特殊情况
if not py[-1].isdigit():
# 为非数字结尾的拼音添加数字声调1
return py + '1'
base = py[:-1] # 去掉声调
tone = int(py[-1]) # 获取声调
# 处理轻声（通常用5表示）或无效声调
if tone not in [1, 2, 3, 4]:
return base + str(random.choice([1, 2, 3, 4]))
# 正常处理声调
possible_tones = [1, 2, 3, 4]
possible_tones.remove(tone) # 移除原声调
new_tone = random.choice(possible_tones) # 随机选择一个新声调
return base + str(new_tone)
def _calculate_replacement_probability(self, orig_freq, target_freq):
"""
根据频率差计算替换概率
"""
if target_freq > orig_freq:
return 1.0 # 如果替换字频率更高，保持原有概率
freq_diff = orig_freq - target_freq
if freq_diff > self.max_freq_diff:
return 0.0 # 频率差太大，不替换
# 使用指数衰减函数计算概率
# 频率差为0时概率为1，频率差为max_freq_diff时概率接近0
return math.exp(-3 * freq_diff / self.max_freq_diff)
def _get_similar_frequency_chars(self, char, py, num_candidates=5):
"""
获取与给定字频率相近的同音字，可能包含声调错误
"""
homophones = []
# 有一定概率使用错误声调
if random.random() < self.tone_error_rate:
wrong_tone_py = self._get_similar_tone_pinyin(py)
homophones.extend(self.pinyin_dict[wrong_tone_py])
# 添加正确声调的同音字
homophones.extend(self.pinyin_dict[py])
if not homophones:
return None
# 获取原字的频率
orig_freq = self.char_frequency.get(char, 0)
# 计算所有同音字与原字的频率差，并过滤掉低频字
freq_diff = [(h, self.char_frequency.get(h, 0))
for h in homophones
if h != char and self.char_frequency.get(h, 0) >= self.min_freq]
if not freq_diff:
return None
# 计算每个候选字的替换概率
candidates_with_prob = []
for h, freq in freq_diff:
prob = self._calculate_replacement_probability(orig_freq, freq)
if prob > 0: # 只保留有效概率的候选字
candidates_with_prob.append((h, prob))
if not candidates_with_prob:
return None
# 根据概率排序
candidates_with_prob.sort(key=lambda x: x[1], reverse=True)
# 返回概率最高的几个字
return [char for char, _ in candidates_with_prob[:num_candidates]]
def _get_word_pinyin(self, word):
"""
获取词语的拼音列表
"""
return [py[0] for py in pinyin(word, style=Style.TONE3)]
def _segment_sentence(self, sentence):
"""
使用jieba分词，返回词语列表
"""
return list(jieba.cut(sentence))
def _get_word_homophones(self, word):
"""
获取整个词的同音词，只返回高频的有意义词语
"""
if len(word) == 1:
return []
# 获取词的拼音
word_pinyin = self._get_word_pinyin(word)
# 遍历所有可能的同音字组合
candidates = []
for py in word_pinyin:
chars = self.pinyin_dict.get(py, [])
if not chars:
return []
candidates.append(chars)
# 生成所有可能的组合
import itertools
all_combinations = itertools.product(*candidates)
# 获取jieba词典和词频信息
dict_path = os.path.join(os.path.dirname(jieba.__file__), 'dict.txt')
valid_words = {} # 改用字典存储词语及其频率
with open(dict_path, 'r', encoding='utf-8') as f:
for line in f:
parts = line.strip().split()
if len(parts) >= 2:
word_text = parts[0]
word_freq = float(parts[1]) # 获取词频
valid_words[word_text] = word_freq
# 获取原词的词频作为参考
original_word_freq = valid_words.get(word, 0)
min_word_freq = original_word_freq * 0.1 # 设置最小词频为原词频的10%
# 过滤和计算频率
homophones = []
for combo in all_combinations:
new_word = ''.join(combo)
if new_word != word and new_word in valid_words:
new_word_freq = valid_words[new_word]
# 只保留词频达到阈值的词
if new_word_freq >= min_word_freq:
# 计算词的平均字频（考虑字频和词频）
char_avg_freq = sum(self.char_frequency.get(c, 0) for c in new_word) / len(new_word)
# 综合评分：结合词频和字频
combined_score = (new_word_freq * 0.7 + char_avg_freq * 0.3)
if combined_score >= self.min_freq:
homophones.append((new_word, combined_score))
# 按综合分数排序并限制返回数量
sorted_homophones = sorted(homophones, key=lambda x: x[1], reverse=True)
return [word for word, _ in sorted_homophones[:5]] # 限制返回前5个结果
def create_typo_sentence(self, sentence):
"""
创建包含同音字错误的句子，支持词语级别和字级别的替换
参数:
sentence: 输入的中文句子
返回:
typo_sentence: 包含错别字的句子
typo_info: 错别字信息列表
"""
result = []
typo_info = []
# 分词
words = self._segment_sentence(sentence)
for word in words:
# 如果是标点符号或空格，直接添加
if all(not self._is_chinese_char(c) for c in word):
result.append(word)
continue
# 获取词语的拼音
word_pinyin = self._get_word_pinyin(word)
# 尝试整词替换
if len(word) > 1 and random.random() < self.word_replace_rate:
word_homophones = self._get_word_homophones(word)
if word_homophones:
typo_word = random.choice(word_homophones)
# 计算词的平均频率
orig_freq = sum(self.char_frequency.get(c, 0) for c in word) / len(word)
typo_freq = sum(self.char_frequency.get(c, 0) for c in typo_word) / len(typo_word)
# 添加到结果中
result.append(typo_word)
typo_info.append((word, typo_word,
' '.join(word_pinyin),
' '.join(self._get_word_pinyin(typo_word)),
orig_freq, typo_freq))
continue
# 如果不进行整词替换，则进行单字替换
if len(word) == 1:
char = word
py = word_pinyin[0]
if random.random() < self.error_rate:
similar_chars = self._get_similar_frequency_chars(char, py)
if similar_chars:
typo_char = random.choice(similar_chars)
typo_freq = self.char_frequency.get(typo_char, 0)
orig_freq = self.char_frequency.get(char, 0)
replace_prob = self._calculate_replacement_probability(orig_freq, typo_freq)
if random.random() < replace_prob:
result.append(typo_char)
typo_py = pinyin(typo_char, style=Style.TONE3)[0][0]
typo_info.append((char, typo_char, py, typo_py, orig_freq, typo_freq))
continue
result.append(char)
else:
# 处理多字词的单字替换
word_result = []
for i, (char, py) in enumerate(zip(word, word_pinyin)):
# 词中的字替换概率降低
word_error_rate = self.error_rate * (0.7 ** (len(word) - 1))
if random.random() < word_error_rate:
similar_chars = self._get_similar_frequency_chars(char, py)
if similar_chars:
typo_char = random.choice(similar_chars)
typo_freq = self.char_frequency.get(typo_char, 0)
orig_freq = self.char_frequency.get(char, 0)
replace_prob = self._calculate_replacement_probability(orig_freq, typo_freq)
if random.random() < replace_prob:
word_result.append(typo_char)
typo_py = pinyin(typo_char, style=Style.TONE3)[0][0]
typo_info.append((char, typo_char, py, typo_py, orig_freq, typo_freq))
continue
word_result.append(char)
result.append(''.join(word_result))
return ''.join(result), typo_info
def format_typo_info(self, typo_info):
"""
格式化错别字信息
参数:
typo_info: 错别字信息列表
返回:
格式化后的错别字信息字符串
"""
if not typo_info:
return "未生成错别字"
result = []
for orig, typo, orig_py, typo_py, orig_freq, typo_freq in typo_info:
# 判断是否为词语替换
is_word = ' ' in orig_py
if is_word:
error_type = "整词替换"
else:
tone_error = orig_py[:-1] == typo_py[:-1] and orig_py[-1] != typo_py[-1]
error_type = "声调错误" if tone_error else "同音字替换"
result.append(f"原文：{orig}({orig_py}) [频率：{orig_freq:.2f}] -> "
f"替换：{typo}({typo_py}) [频率：{typo_freq:.2f}] [{error_type}]")
return "\n".join(result)
def set_params(self, **kwargs):
"""
设置参数
可设置参数:
error_rate: 单字替换概率
min_freq: 最小字频阈值
tone_error_rate: 声调错误概率
word_replace_rate: 整词替换概率
max_freq_diff: 最大允许的频率差异
"""
for key, value in kwargs.items():
if hasattr(self, key):
setattr(self, key, value)
print(f"参数 {key} 已设置为 {value}")
else:
print(f"警告: 参数 {key} 不存在")
def main():
# 创建错别字生成器实例
typo_generator = ChineseTypoGenerator(
error_rate=0.03,
min_freq=7,
tone_error_rate=0.02,
word_replace_rate=0.3
)
# 获取用户输入
sentence = input("请输入中文句子：")
# 创建包含错别字的句子
start_time = time.time()
typo_sentence, typo_info = typo_generator.create_typo_sentence(sentence)
# 打印结果
print("\n原句：", sentence)
print("错字版：", typo_sentence)
# 打印错别字信息
if typo_info:
print("\n错别字信息：")
print(typo_generator.format_typo_info(typo_info))
# 计算并打印总耗时
end_time = time.time()
total_time = end_time - start_time
print(f"\n总耗时：{total_time:.2f}秒")
if __name__ == "__main__":
main()