Deep Convolutional Networks for Supervised Morpheme Segmentation of Russian Language
The present paper addresses the task of morphological segmentation for Russian language. We show that deep convolutional neural networks solve this problem with F1-score of 98% over morpheme boundaries and beat existing non-neural approaches.
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