Noise-robust scream detection using band-limited spectral entropy

This report describes scream detection systems that can detect screams under noisy conditions and describes techniques for increasing their noise-robustness. More specifically, spectral entropy, which expresses the difference in frequency distribution between a scream and noise, is used as a detection feature. Furthermore, a method is presented that improves scream detection accuracy in noisy environments by limiting the frequency band of the spectral entropy used as the detection feature. Evaluation experiments in noisy environments demonstrated that the proposed method has better scream detection capability than a conventional method. The proposed method can detect screams with equal error rates of 0.3% and 0.8% under 0 and −5 dB conditions, respectively. Furthermore, the cost of likelihood calculation is about 1/12th that of the conventional method. The proposed method can thus be used to develop a scream detection system that is sufficiently accurate in an actual environment.