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The Study of Effect of Length in Morphological Segmentation of Agglutinative Languages

机译:凝集语言形态分割的长度效果研究

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Morph length is one of the indicative feature that helps learning the morphology of languages, in particular agglutinative languages. In this paper, we introduce a simple unsupervised model for morphological segmentation and study how the knowledge of morph length affect the performance of the segmentation task under the Bayesian framework. The model is based on (Goldwater et al., 2006) unigram word segmentation model and assumes a simple prior distribution over morph length. We experiment this model on two highly related and agglutinative languages namely Tamil and Telugu, and compare our results with the state of the art Mor-fessor system. We show that, knowledge of morph length has a positive impact and provides competitive results in terms of overall performance.
机译:变形长度是有助于学习语言形态,特别是凝集语言的指示特征之一。在本文中,我们介绍了一个简单的无监督模型,用于形态分割,研究变形长度的知识如何影响贝叶斯框架下分割任务的性能。该模型基于(Goldwater等,2006)Unigram字分割模型,并假设Morph长度的简单先前分布。我们在两种高度相关和凝聚的语言中尝试这种模型,即泰米尔和泰卢固定,并将我们的结果与艺术艺术Mor-Fessor系统的结果进行比较。我们表明,理解变形长度具有积极的影响,并在整体表现方面提供竞争力。

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