Suspicious Behavior Detection from Speech: A Proof of Concept

The goal of this study is to contribute on the development of human-machine interface that helps to identify individuals with suspicious behavior (of violence, terrorism,…) from speech.To do it, it was neceassry to define suspicious behavior through emotions according to valence and activation. Next, a scenario including background noise, security agent speech and vistor speech was defined. A dataset was constructed, speech processing and machine learning based algorithms are designed: after features extraction, audio stream is segmented into relevant content (noise, agent speech and visitor speech). The visitor speech is selected and a classification is carried to detect suspicious behavior. Simulation results show the effectiveness of the proposed solution.