论文标题

Sigmorphon 2020的IMS-Cuboulder系统共享无监督的形态范式完成任务

The IMS-CUBoulder System for the SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion

论文作者

Mager, Manuel, Kann, Katharina

论文摘要

在本文中,我们介绍了斯图加特大学IMS大学和科罗拉多大学博尔德大学(IMS-Cuboulder)的Sigmorphon 2020 Task 2在无监督的形态范式上完成(Kann等,2020)。该任务包括产生一组引理的形态范例,只有鉴于引理本身和未标记的文字。我们提出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产生成分。我们的Pointer-Generator系统平均获得了所有七个提交系统的最佳分数,并且在保加利亚和卡纳达语上超过了官方基线,这是最好的基线。

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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