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CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology

机译:CMU-01在SIGMORPHON 2019形态学中的跨语言和语境共享任务

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This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lemma and morpho-syntactic description of each token in a sequence, for 107 treebanks. We approach this task with a hierarchical neural conditional random field (CRF) model which predicts each coarse-grained feature (eg. POS. Case, etc.) independently. However, most treebanks are under-resourced, thus making it challenging to train deep neural models for them. Hence, we propose a multi-lingual transfer training regime where we transfer from multiple related languages that share similar typology.~1
机译:本文介绍了CMU-01团队提交给SIGMORPHON 2019任务2的情境形态分析和词法化的内容。此任务需要我们为107个树库生成序列中每个标记的引理和句法语法描述。我们使用分层的神经条件随机场(CRF)模型来完成这项任务,该模型可以独立预测每个粗粒度特征(例如POS,Case等)。但是,大多数树库资源不足,因此为它们训练深层神经模型具有挑战性。因此,我们提出了一种多语种的迁移培训制度,即从具有相似类型的多种相关语言进行迁移。〜1

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