Fear-type emotion recognition and abnormal events detection for an audio-based surveillance system
Chloé Clavel, T. Ehrette · WIT transactions on information and communication technologies · 2008
The goal of our research work is to carry out an audio-based abnormal situation diagnosis system for the SERKET project which aims at developing surveillance systems dealing with dispersed data coming from heterogeneous sensors.We look at things from the point of view of human life protection in the context of civil safety.Therefore, we focus on abnormal situations during which human life is threatened (psychological and physical attack).The proposed system relies on information conveyed by both speech and non-speech acoustic manifestations to generate alerts.More precisely, our audio module can be divided into two sub-modules.The first one concerns the abnormal event detection system that is illustrated here in the case of gun-shot.The second one focuses on information conveyed by the emotional content of speech.Such information is useful for decoding human behaviour in abnormal situations and so provides a situation diagnosis.More precisely the targeted emotions are fear-type emotions corresponding to symptomatic emotions occurring when the matter of survival is raised, including the different fear-related emotional states from worry to panic.At the last stage of its development, this work would propose a surveillance system plugged into a real control room.Thus, we proposed here a mock-up to illustrate the running of these two systems.