INLI@FIRE-2018: A Native Language Identification System using Convolutional Neural Networks

In general, the spectrogram of bird sound audio is regarded as the input and the model would treat the bird-call identification task as an image classification problem.. This

We present a three-layer convolutional neural network for the classification of two binary target variables ’Social’ and ’Agency’ in the HappyDB corpus exploiting lexical density of

The article describes the dataset developed for the classifier training, the algorithm for data preprocessing, described an architecture of a convolutional neural network for

The classifier has been used with three differ- ent strategies (i.e. One-vs-the-rest and Pairwise Coupling strategies as described in [7]) and achieved an accuracy of 42.1% for

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

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 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