Author's implementation of the paper https://www.aclweb.org/anthology/2021.dravidianlangtech-1.30/

Author's implementation of the paper https://www.aclweb.org/anthology/2021.ltedi-1.30/

In order to encourage constructive online debates, content control is crucial on social media sites. In this group project, participants are asked to create systems to handle offensive stretches of code-mixed social media material in Tamil.

Contextualized Topic Modeling using Zero-Shot Learning on Indic Languages (IndicCTM)

Understanding the sentiment of customers from product reviews using IndicBERT

Online gender-based violence limits marginalized voices. Detection in Indic languages is hard due to limited data and linguistic complexity. This work builds better classifiers for improved abuse detection in such settings.

Developed an SRL system using statistical and neural models to label semantic roles in Hindi sentences. Achieved up to 95.34% accuracy using IndicBERT and BiLSTM. Includes datasets, code, and model files.

A python package to run contextualized topic modeling for Indic Languages. indicCTMs combine contextualized embeddings (e.g., IndicBERT) with topic models to get coherent topics in Hindi, English, and Tamil.

This repository contains the implementation of a transfer learning-based approach for detecting AI-generated product reviews in Tamil and Malayalam. It includes pretrained model embeddings, deep neural networks, and an ensemble method to enhance classification accuracy.

Online gender-based violence limits marginalized voices. Detection in Indic languages is hard due to limited data and linguistic complexity. This work builds better classifiers for improved abuse detection in such settings.