Acoustic Scene Change Detection by Spectro-Temporal Filtering on Spectrogram using Chirps

Abstract

Indoor acoustic scene change detection systems using periodic impulse signals were developed in the past. Comparing with impulse signals, the chirp signal is more robust against environmental noise due to its specific spectro-temporal structure, which can be easily detected using a spectro-temporal modulation filtering mechanism. In this paper, we demonstrate a system which employs the two-dimensional spectro-temporal filtering mechanism on Fourier spectrogram to measure the total energy of reverberations of the chirp signal and compares the energy difference between consecutive chirps with a predefined threshold to automatically detect the change of the acoustic scene. Simulation results show the proposed system is very effective in detecting the acoustic scene change in a real living room with great robustness against noise recorded from real-world.