Deep convolutional networks for supervised morpheme segmentation of Russian language

Alexey Sorokin, Anastasia Kravtsova

Abstract: 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.