An indoor acoustic scene monitoring system using a periodic impulse signal was previously developed. Compared with the impulse signal, the chirp signal is more robust against environmental noise due to its specific spectro-temporal structure. Such specific structure makes the chirp sound easily detected using a spectro-temporal modulation filtering mechanism. In this paper, we demonstrated a system that employs a two-dimensional spectro-temporal filtering mechanism on a Fourier spectrogram to measure the total energy of the reverberations of the chirp signal as the representation of the acoustic scene. The system compares the reverberation energy difference between consecutive chirps with a predefined threshold to automatically detect the change in the acoustic scene. Simulations were conducted in real living rooms with various types of background noise. Test results demonstrated that the proposed system is much more effective than previously developed systems for detecting the acoustic scene changes due to the intruder silently walking in the rooms. In the biggest test room (18 × 9.8 × 2.5 m3) with heavy background noise, the proposed system can still yield a correct identification rate higher than 80% to the intruder walking at 7 m from the microphone without producing any false alarms.