Perceptually motivated temporal modeling of footsteps in a cross-environmental detection task

Real world sounds are ubiquitous and form an important part of the edifice of our cognitive abilities. Their perception combines signatures from spectral and temporal domains, among others, yet traditionally their analysis is focused on the frame based spectral properties. We consider the problem of sound analysis from perceptual perspective and investigate the temporal properties of a “footsteps” sound, which is a particularly challenging from the time-frequency analysis viewpoint. We identify the irregular repetition of the self similarity and the sense of duration as significant to its perceptual quality and extract features using the Teager-Kaiser energy operator. We build an acoustic event detection system for “footsteps” which shows promising results for detection in cross-environmental conditions when compared with conventional approach.