A system to prevent social violence using convolutional neural network

Abstract

Most women face violence in public and at home, including rape, physical and emo tional abuse, mocking, and harassment. A social violence support system might allow people to seek aid from their friends, or relatives, or even request administra tive assistance. The goal here is to detect clearly and reliably the screams of the individual in the position that is in any danger, that is, if the scream arose out of dread and horror, based on a particular collection of audios. Screams elicited by dread and panic usually have a shorter length, a higher frequency, and shrill pitches, whereas screams elicited by other emotions or intentionally have a longer duration, a fixed frequency, and pitch. In this sense, if we can use scream recognition to recognize dangerous and consequential circumstances in our society and inform the appropriate individuals at the appropriate moment, we will be able to avert these issues to a degree that will benefit both society and its citizens. To assist the wider populace, we have implemented a system using Convolutional Neural Network to identify screams automatically. This model will assist us in recognizing screams and sending SOS signals or messages to suitable contacts. As a result, people who are in danger will be able to call the people from their selected contacts or general authorities who are within their reach at any time. This system will not only assist victims in avoiding danger, but it will also provide them with a sense of security. On the other hand, the general authority will be able to use this software to limit the quantity of social and domestic violence.