Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Chinese
Size:
10K - 100K
ArXiv:
License:
Upload clean_data.py
Browse files- sentence_data/clean_data.py +64 -0
sentence_data/clean_data.py
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# 把该py文件的 ./transcript 文件夹下面的所有文件依次取出来,
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# 看看是否包含()这个符号,付过包含,打印出来,并且把()和他里面的内容删除,把处理好的文本放回原文件之中
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import os
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import re
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def clean_line(line):
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result = [] # 用于存储清洗后的字符
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in_brackets = False # 标记是否在括号内
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for char in line:
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if char == '(':
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# 遇到左括号,标记为在括号内
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in_brackets = True
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elif char == ')':
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# 遇到右括号,标记为不在括号内
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in_brackets = False
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elif not in_brackets:
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# 如果不在括号内,保留字符
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result.append(char)
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# 将字符列表拼接成字符串并返回
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return ''.join(result)
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def process_files(folder_path):
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"""
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遍历指定文件夹中的所有文件,逐行清洗包含括号的文本,并将结果写回原文件。
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"""
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# 检查文件夹是否存在
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if not os.path.exists(folder_path):
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print(f"文件夹 {folder_path} 不存在!")
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return
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# 遍历文件夹中的所有文件
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for file_name in os.listdir(folder_path):
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file_path = os.path.join(folder_path, file_name)
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# 确保是文件而不是子文件夹
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if os.path.isfile(file_path):
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try:
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# 创建临时文件
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temp_file_path = file_path + ".tmp"
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with open(file_path, 'r', encoding='utf-8') as infile, open(temp_file_path, 'w', encoding='utf-8') as outfile:
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# 逐行读取文件
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for line in infile:
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# 清洗当前行
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cleaned_line = clean_line(line)
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# 写入清洗后的行到临时文件
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outfile.write(cleaned_line)
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# 替换原文件
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os.replace(temp_file_path, file_path)
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print(f"已清洗并保存到: {file_name}")
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except Exception as e:
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print(f"处理文件 {file_name} 时出错: {e}")
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if __name__ == "__main__":
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# 指定文件夹路径
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transcript_folder = "./transcript"
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# 调用函数处理文件
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process_files(transcript_folder)
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