Toxicity Detection in Speech

Abstract

Speech is a fundamental source of communication. We express our ideas, thoughts, and sentiments through speech. What we say (our speech) has a very significant effect on our personalities and the personalities of our listeners. A positive speech spreads positivity in society, gives peace to its speaker and pleasure to the listeners. On the other hand, negative or toxic speech cause great damage to our society. It not only has a negatively effects the minds of the speaker and listener but also spoils their personalities. Ultimately toxic conversation reshapes human personality in such a way that might leads speakers and listeners to get involved in toxic actions. So, it is momentous to put a stop to these toxic conversations in our society. According to the best of our knowledge, there is no existing system that can classify a digital audio conversation (digital speech) as toxic or normal. To fulfil this gap, we have built an administrative android mobile app that will notify the parent whenever an audio speech is classified as toxic. This will allow parent to guide their children to avoid having such toxic conversations. Using the digital audio data of day-to-day conversations, we have trained a Machine Learning model, and using the REST API call, we will send audio to the model and in response, we get a prediction of whether the audio is toxic or normal. In the case of Toxicity, a notification is dispatched to the parent to notify them that a toxic conversation is detected.