As regular CFZ-watchers will know, for some time Corinna has been doing a column for Animals & Men and a regular segment on On The Track... particularly about out-of-place birds and rare vagrants. There seem to be more and more bird stories from all over the world hitting the news these days so, to make room for them all - and to give them all equal and worthy coverage - she has set up this new blog to cover all things feathery and Fortean.

Sunday, 7 August 2016

Scientists are using sound to track nighttime bird migration

Last Updated by Adam Wernick on Aug 02, 2016 at 2:44 pm 

A group of researchers at New York University and the Cornell Lab of Ornithology are helping to track the nighttime migratory patterns of birds by teaching a computer to recognize their flight calls.

The technique, called acoustic monitoring, has existed for some time, but the development of advanced computer algorithms may provide researchers with better information than they have gathered in the past.

“We want to make as many different kinds of measurements as we can,” says Andrew Farnsworth, of the Cornell Lab of Ornithology. “The intro point to go from human to computer is about thinking of these sounds in terms of frequency and time, and figuring out how to measure that in increasing detail and feed that information into the machine’s listening models.”

“On the sensors, there is a spectral template detector that scans the audio as it comes in, checking for potential matches,” explains Justin Solomon of NYU, one of the collaborators on the project. “When a potential match is identified, it snaps roughly one second of that audio centered around the detection and sends that through the server.”

Flight calls are distinct from birdsong. Birdsong is made up of many different notes strung together. Flight calls are single notes, almost exclusively less than one hundred milliseconds long. The researchers ‘teach’ the machine to recognize these calls by giving it a large collection of recordings.

Then they use what's called ‘unsupervised feature learning,’ which means that they don't tell the algorithm what to look for. Rather, by giving it a large number of examples, the computer builds a statistical model of the specific patterns that are representative of a certain species.

The eventual goal is to be able to put names to these nocturnally-migrating species and do it in an automated way in real time, in order to understand the biology — the acoustic communication — and apply it to conservation.

Right now, scientists use two sources of information when trying to understand migratory patterns. The first is bird watchers — many people watching birds all across the country. Cornell has been good at gathering information from citizen scientists who help categorize the occurrence of certain species by location and time. But those observations are mostly made by day, and migrations often occur at night.

No comments:

Post a Comment