ISI at the Sigmorphon 2017 shared task on morphological reinflection

Abstract

We present a system for morphological reinflection based on the LSTM model. Given an input word and morphosyntactic descriptions, the problem is to classify the proper edit tree that, applied on the input word, produces the target form. The proposed method does not require human defined features and it is language independent also. Currently, we evaluate our system only for task 1 without using any external data. From the test set results, it is found that the proposed model beats the baseline on 15 out of the 52 languages in high resource scenario. But its performance is poor when the training set size is medium or low.