The library integrates voice-based offensive content detection in iOS apps, utilizing Apple's Speech framework and a machine learning model created with Create ML. It accurately identifies offensive language and hate speech, supporting both SwiftUI and UIKit for content moderation.

Detection of Offensive Language and Toxic Content in Tweets Using Word Embeddings, the OLID and SOLID Datasets, and LIME Visualizations for Enhanced Interpretability.

Paper: A Cancel Culture Corpus through the lens of Natural Language Processing

Example dataset and prompt design of Korean Offensive language Machine Generation (K-OMG), published at IJCNLP-AACL 2023.

Pytorch code for "Multilingual Offensive Language Identification"

This repository contains resources for aggression and offensive language detection, for our WOAH 2023 publication.

Offensive language exploratory analysis

A framework for adapting Pretrained Language Models (XLM-R, BERT etc.) for Low-Resourced Offensive Language Detection in Sinhala using pretrained models and intermediate tasks.

WhatsApp Multiplexer - An automation tool for WhatsApp web

Our submission to OffensEval 2020 to classify offensive language in social media tweets, where we ranked #15.

Translated abusive language dataset (En2Ko). Including OffensEval/AbusEval, CADD, Davidson et al., Waseem&Hovy.

Multidimensional Affective Analysis for Guarani/Jopara

Machine Learning project automating the detection of comments that violate YouTube's community guidelines.