A proposal of a knowledge based isolated word recognition

S. Morishima, H. Harashima, H. Miyakawa
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引用次数: 11

Abstract

This paper describes a knowledge based isolated Japanese word recognition algorithm. The program is written with Prolog/KR [4] and has two basic inference processes, i.e., a Bottom-up search and a Top-down search. In the Bottom-up process, a segmentation and a vowel decision are performed and some target word patterns are generated. The Top-down process includes a consonant decision using a score of each candidate word calculated based on the Fuzzy Set Theory [1]. In the vowel inference, a template matching is applied mainly. In the segmentation, heuristic rules based on the spectrum transition and the wave form are used. But in the consonant inference, each rule has a hierarchy structure and it is defined automatically in the form of the multi-valued threshold function from learning data. This system can treat an obscure information about the consonant classification and to select the most effective decision rule in order to simplify the understanding process. The truth rate of consonant recognition is better than using statistical method.
一种基于知识的孤立词识别方法
提出了一种基于知识的日语孤立词识别算法。该程序使用Prolog/KR[4]编写,具有两个基本推理过程,即自下而上搜索和自上而下搜索。在自底向上的过程中,进行分词和元音判断,并生成目标词模式。自上而下的过程包括使用基于模糊集理论计算的每个候选词的分数进行辅音决策[1]。在元音推理中,主要采用模板匹配。在分割中,使用了基于频谱转移和波形的启发式规则。而在辅音推理中,每条规则都具有层次结构,并以多值阈值函数的形式从学习数据中自动定义。该系统可以处理模糊的辅音分类信息,并选择最有效的决策规则,以简化理解过程。辅音识别的正确率优于统计学方法。
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