A Real-Time Implementation of an Acoustic Novelty Detector on the BeagleBoard-xM

Novelty detection consists in recognising events that deviate from normality. This paper presents the implementation of a real-time statistical novelty detector on the BeagleBoard-xM. The application processes an incoming audio signal, extracts Power Normalized Cepstral Coefficients and determines whether a novelty sound is present or not based on a statistical model of normality. The novelty detector has been implemented as a standalone graphical application capable of running in real-time on the BeagleBoard-xM platform. Experiments have been conducted to assess the performance of the solution in terms of both detection performance and of real-time capabilities. The results demonstrate that the system is able to operate in real-time on the BeagleBoard-xM with a real-time factor equal to 8.10%, and an F-Measure equal to 77.41%.