Offensive Language Detection on Telugu Language

In the present world a lot of data is generated via twitter, Instagram, WhatsApp etc. in different languages. It is important and necessary task to detect the offensive language among those data to create healthy and good environment among people. And it is even highly challenging task to identify offensive language in low resource languages due to less availability of the classified datasets. This paper aims to detecting of offensive language on a low resource language Telugu. To identify solution for this problem different types of ML models and DL models are used. Based on accuracy of the different models we are going to choose a model. To split the data and train the data and to test the data we have been using stratified k fold cross validation which is an efficient way to split the data and to increase model’s ability to perform better. From basis of this experiments, we can have a model to detect offensive language in Telugu and it must be considered as a small step for future models to work on it.