'DeepSqueak' Helps Researchers Decode Rodent Chatter

Two scientists at the University of Washington School of Medicine have developed a software program that represents the first use of deep artificial neural networks in squeak detection. University of Washington (UW) School of Medicine researchers have developed a software program to identify and decode rodent vocalizations. The DeepSqueak deep neural network converts audio signals into an image, or sonogram, which could be further refined with machine-vision algorithms developed for self-driving cars. Said the UW School of Medicine's Russell Marx, "DeepSqueak uses biomimetic algorithms that learn to isolate vocalizations by being given labeled examples of vocalizations and noise." According to co-developer Kevin Coffey, the program could distinguish between about 20 kinds of rodent calls.