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

页码：311 / 330

页数：20

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