Verbal Harassment Detection in Online Games Using Machine Learning Methods

Abstract

Video games have been an inseparable aspect for many throughout their upbringing. The widespread adoption of the internet in the early 2000s has brought video games from the traditional offline media to the online environment. Consequently, people from different parts of the world can play together and communicate in-game with each other. Nowadays, most massively multiplayer online games (MMOs) incorporate voice communication features. Playing video games online with a certain degree of anonymity, along with the ability to verbally communicate with each other, has proven to be a dangerous combination that can breed toxic and abusive behaviors if left unmoderated. This paper proposes a new approach to integrating Whisper, a pre-trained automatic speech recognition (ASR) model, with the well-researched topic of text-based abusive behavior detection. Our proposed verbal harassment detection pipelines yielded an average F-score of 0.899 for all variants tested.