Who knew? A few weeks back, we mentioned that Chicago was setting up a series of listening posts, to keep an ear out for gunshots. Well, it turns out that the system, called SENTRI, is based on the way peoples' neurons fire.
SENTRI is an acronym for "Smart Sensor Enabled Neural Threat Recognition and Identification." The "neural" in the title refers directly to [USC Center for Neural Engineering director Theodore] Berger's work, which was based on analysis of the "language" nerve cells, or neurons, use to convey information, and specifically on his modeling of the way the brain forms memories of sounds.
The neurons' only way of distinguishing signals is to fire repeatedly, either faster or slower, in different temporal patterns. "It is the time difference between pulses that carries the information," Berger said. "This is a coding completely unlike that used by computers, which are collections of ones and zeros, changing to the beat of a constant clock."
Working with computer specialists, however, Berger has created neural-like computer systems that can model the neural time coding and make distinctions the way nerves do.
Four years ago, he and a colleague used the technique to demonstrate the first speech recognition system that could pick words out of ambient noise as well as humans can. While work continues on speech-recognition applications, the systems need training to learn individual signals. For language, this is very time consuming because the system has to learn each individual word.
"But for alarm signals," Berger said, "you start with a relatively small number of sounds you have to distinguish with high accuracy - gunshots, for example, or diesel engines for border patrol crossings or oil pipeline thieves, or chainsaws to listen for outlaw loggers. This vocabulary is quite manageable."
(thanks RC for the tip)
