无监督形态范式完成SIGMORPHON 2020共享任务的IMS-CUBoulder系统

Manuel Mager, Katharina Kann
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引用次数: 2

摘要

在本文中,我们介绍了斯图加特大学IMS和科罗拉多大学博尔德分校(IMS- CUBoulder)用于SIGMORPHON 2020任务2的无监督形态范式完成的系统(Kann等人,2020)。该任务包括生成一组引理的形态范式,只给出引理本身和未标记的文本。我们建议的系统是与任务一起引入的基线的修改版本。特别是,我们尝试用LSTM序列到序列模型和LSTM指针生成器网络代替拐点生成组件。在所有语言中,我们的指针生成器系统在所有提交的七个系统中平均得分最高,并且在保加利亚语和卡纳达语方面的表现优于官方基准,而官方基准总体上是最好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The IMS–CUBoulder System for the SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
In this paper, we present the systems of the University of Stuttgart IMS and the University of Colorado Boulder (IMS--CUBoulder) for SIGMORPHON 2020 Task 2 on unsupervised morphological paradigm completion (Kann et al., 2020). The task consists of generating the morphological paradigms of a set of lemmas, given only the lemmas themselves and unlabeled text. Our proposed system is a modified version of the baseline introduced together with the task. In particular, we experiment with substituting the inflection generation component with an LSTM sequence-to-sequence model and an LSTM pointer-generator network. Our pointer-generator system obtains the best score of all seven submitted systems on average over all languages, and outperforms the official baseline, which was best overall, on Bulgarian and Kannada.
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