Improving neural morphological Tagging using Language Models

Abstract

This paper addresses the task of morphological tagging and demonstrates how neural network architectures bene t from using language models for morphological tags. We show that incorporating the probabilities from language model on morphological tags improves the quality of character-based morphological tagging, reducing the error by 10%.

Tasks

Reproductions