SSN_NLP@INLI-FIRE-2017: A Neural Network Approach to Indian Native Language Identification

Native Language Identification (NLI) is the process of identifying the native language of non-native speakers based on their speech or writing. It has several applications namely authorship profiling and identification, forensic analysis, second language identification, and educational applications. English is one of the prominent language used by most of the non-English people in the world. The native language of the non-English speakers may be easily identified based on their English accents. However, identification of native language based on the users posts and comments written in English is a challenging task. In this paper, we present a neural network approach to identify the native language of an Indian speaker based on the English comments that are posted in microblogs. The lexical features are extracted from the text posted by the user and are used to build a neural network classifier to identify the native language of the user. We have evaluated our approach using the data set given by INLI@FIRE2017 shared task.