A Language-aware Approach to Code-switched Morphological Tagging
Şaziye Betül Özateş, Özlem Çetinoğlu · 2021
Morphological tagging of code-switching (CS) data becomes more challenging especially when language pairs composing the CS data have different morphological representations.In this paper, we explore a number of ways of implementing a language-aware morphological tagging method and present our approach for integrating language IDs into a transformerbased framework for CS morphological tagging.We perform our set of experiments on the Turkish-German SAGT Treebank.Experimental results show that including language IDs to the learning model significantly improves accuracy over other approaches.