#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright 2021 Xiaomi Corp. (authors: Mingshuang Luo) # # See ../../../../LICENSE for clarification regarding multiple authors # # 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. """ This script takes as input "text", which refers to the transcript file for WenetSpeech: - text and generates the output file text_word_segmentation which is implemented with word segmenting: - text_words_segmentation """ import argparse import jieba import paddle from tqdm import tqdm paddle.enable_static() jieba.enable_paddle() def get_parser(): parser = argparse.ArgumentParser( description="Chinese Word Segmentation for text", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "--input-file", default="data/lang_char/text", type=str, help="the input text file for WenetSpeech", ) parser.add_argument( "--output-file", default="data/lang_char/text_words_segmentation", type=str, help="the text implemented with words segmenting for WenetSpeech", ) return parser def main(): parser = get_parser() args = parser.parse_args() input_file = args.input_file output_file = args.output_file f = open(input_file, "r", encoding="utf-8") lines = f.readlines() new_lines = [] for i in tqdm(range(len(lines))): x = lines[i].rstrip() seg_list = jieba.cut(x, use_paddle=True) new_line = " ".join(seg_list) new_lines.append(new_line) f_new = open(output_file, "w", encoding="utf-8") for line in new_lines: f_new.write(line) f_new.write("\n") if __name__ == "__main__": main()