Surveillance Applications in non-Stationary Acoustic Environments - SALSA
This group has experience in the analysis of sound scenes, both in closed and open spaces, having developed algorithms to integrate a set of techniques for locating, separating and classifying acoustic signals.
During SSPressing project, two different acoustic nodes were designed: a node with no power limitations and high computing features, based on Raspberry Pi; and a low consumption, low cost, self-contained node that does not require external power, with reduced computing capacity, using batteries that are charged by solar cells, and using ultra low power DSPs technology . This solar powered node has a low consumption ARM STM32F4 processor, 4 MEMS microphones, and sub 1-GHz communication capabilities, and it was used to successfully implement a violence detection system.
This group shows deep experience in signal processing algorithms for audiological applications and design of digital hearing aids: algorithms for acoustic environment classification, speech intelligibility enhancement using source separation techniques [Ayl13], optimization of low power consumption algorithms, have been proposed and reported by publications. This team has also shown experience in detecting impulsive sources, such as gunshots [San17b], using array processing algorithms.