Corplab INLI@FIRE-2018: Identification of Indian Native Language using Pairwise Coupling

Native Language Identification (NLI) is the task of classifying the native lan- guage (L1) of an individual into given different languages based on his/her writ- ing in another

The assumption is that, bidirectional LSTM can capture the entire document features regarding language model into x word dt and n-gram features for convolu- tional neural network into

In this paper, we propose to use Hyperdimensional Computing (HDC) as supervised learning for identifying Indian Native Languages from the user’s social media comments written

Given a corpus with comments in English from various Facebook newspapers pages, the objective of the task is to identify the na- tive language among the following six Indian

We submitted two systems using Support Vector Machine (SVM) and Ensemble Classifier based on three different classifiers representing the comments (data) as vector space model for

We have ex- tracted TF-IDF feature vectors from the given document and used SVM classifier to identify the native language of the document given by shared task on Indian Native

The set of BOW features along with the class labels namely Tamil, Hindi, Kannada, Malayalam, Bengali and Telugu from training data are used to build a model using a simple

For every language, frequencies are relativized by dividing individual tri-gram counts through the number of all tri-grams in the training corpus and are sorted based on