Analysis of Myanmar Word boundary and segmentation by using Statistical Approach

A. M. Mon, M. Thein, S. S. Htay, Soe Lai Phyue, Thinn Thinn Win
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引用次数: 8

Abstract

This paper proposed a unified approach for Myanmar Word analysis using Finite State Automata (FSA), Rule Based Heuristic Approach and Statistical Approach. Myanmar has no inter-word space and it make the tokenizing task difficulties. Therefore, to recognize the word, we implement with FSA. Segmentation is a major problem because of no delimiter. If there were errors in segmentation, this will cause subsequence failure in further NLP processes. Segmentation is also an essential preprocessing task for Natural Language Processing, such as Machine Translation, Information Retrieval etc. In this system, the Rule Based Heuristic Approach and Statistical Approach are used with corpus based dictionary. Evaluation results showed that the method is very effective for the Myanmar language.
基于统计方法的缅甸语词边界及分词分析
本文提出了一种基于有限状态自动机(FSA)、基于规则的启发式方法和统计方法的缅甸语词统一分析方法。缅甸语没有词间空间,这给标记化任务带来了困难。因此,为了识别单词,我们使用FSA来实现。由于没有分隔符,分割是一个主要问题。如果在分割中出现错误,这将导致后续NLP处理的失败。分词也是机器翻译、信息检索等自然语言处理中必不可少的预处理任务。该系统采用了基于规则的启发式方法和基于语料库的词典统计方法。评价结果表明,该方法对缅甸语的学习是非常有效的。
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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