Unsupervised morphological parsing of Bengali

被引：15
|
作者：
Dasgupta, Sajib [1 ]
Ng, Vincent [1 ]
机构：
[1] Univ Texas, Human Language Technol Res Inst, Richardson, TX 75083 USA
来源：
LANGUAGE RESOURCES AND EVALUATION | 2006年 / 40卷 / 3-4期
关键词：
morphological parsing; word segmentation; data annotation; unsupervised learning; Asian language processing; Bengali;
D O I：
10.1007/s10579-007-9031-y
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Unsupervised morphological analysis is the task of segmenting words into prefixes, suffixes and stems without prior knowledge of language-specific morphotactics and morpho-phonological rules. This paper introduces a simple, yet highly effective algorithm for unsupervised morphological learning for Bengali, an Indo-Aryan language that is highly inflectional in nature. When evaluated on a set of 4,110 human-segmented Bengali words, our algorithm achieves an F-score of 83%, substantially outperforming Linguistica, one of the most widely-used unsupervised morphological parsers, by about 23%.
引用
收藏
页码：311 / 330
页数：20
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