Parallel Text Identification Using Lexical and Corpus Features for the English-Maori Language Pair

Mahsa Mohaghegh, A. Sarrafzadeh
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引用次数: 2

Abstract

Comparable corpora contain significant quantities of useful data for Natural Language Processing tasks, especially in the area of Machine Translation. They are mainly the source of parallel text fragments. This paper investigates how to effectively extract bilingual texts from comparable corpora relying on a small-size parallel training corpus. We propose a new technique to filter non parallel articles in Wikipedia based on Zipfian frequency distribution. We also use the SVM approach to find parallel chunks of text in a candidate comparable document. In our approach we use a parallel corpus to generate the required features for the training step. The evaluations of generated bilingual texts are promising.
基于词汇和语料库特征的英语-毛利语对平行文本识别
可比较的语料库包含大量对自然语言处理任务有用的数据,特别是在机器翻译领域。它们主要是平行文本片段的来源。本文基于一个小型的平行训练语料库,研究了如何从可比语料库中有效地提取双语文本。提出了一种基于Zipfian频率分布的维基百科非并行条目过滤方法。我们还使用支持向量机方法在候选可比文档中查找并行文本块。在我们的方法中,我们使用并行语料库来生成训练步骤所需的特征。生成的双语文本的评价是有前景的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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