Juan Pablo Bello, associate professor of music technology and director of the Music and Audio Research Lab (MARL) at the NYU Steinhardt School of Culture, Education and Human Development, was awarded a grant of over $600,0000 by the National Science Foundation (NSF) to research and refine emerging machine listening technologies to identify different species of birds during migration.
The award falls under a larger $1.5 million Big Data program grant, awarded to the project, BirdVox: Automatic Bird Species Identification from Flight Calls,” conducted jointly by NYU and the Cornell Lab of Ornithology (CLO), who lead the project.
Collecting reliable, real-time data on the migratory patterns of birds can help foster more effective conservation practices, and – when correlated with other data - provide insight into important environmental phenomena. Scientists at CLO currently rely on information from weather surveillance radar, as well as reporting data from over 400,000 active birdwatchers, one of the largest and longest-standing citizen science networks in existence. However, there are important gaps in this information since radar imaging cannot differentiate between species, and most birds migrate at night, unobserved by citizen scientists. The combination of acoustic sensing and machine listening in this project addresses these shortcomings, providing valuable species-specific data that can help biologists complete the bird migration puzzle.
“Our technology can be trained to differentiate between the calls of, for example, a sparrow, an ovenbird or a cardinal, and scaled up to process data from hundreds of sensors at a time,” said Bello. “This will result in real time migratory information on exactly when, where, and which specific birds are migrating over the sensed area.”
Millions of birds die every year in collisions with infrastructure such as wind farms, buildings and airports during peak migration season, a significant ecological issue that can – depending on the species of bird – also result in accidents and costly downtime for infrastructure on the ground. Thus the technologies developed under the BirdVox project have the potential not only to advance science, but also to the development of early-warning systems and other engineering solutions intended to address those problems.
“This collaboration is really a perfect partnership because it serves a critical function in advancing the research of both labs,” said Steve Kelling, CLO’s senior director of information science and technology. “CLO has a great set up for collecting and annotating the large amounts of data needed to train and benchmark machine learning algorithms, and also provides the domain knowledge needed to optimally explore the space of applications of the technologies. MARL’s expertise in sound analysis and the development of smart sensing technologies will not only fill a void in our research, but open new doors to what we can attempt in the future.”
The BirdVox team also includes Andrew Farnsworth, research associate at CLO and Justin Salamon, a postdoctoral associate at MARL and NYU’s Center for Urban Science and Progress.
For more information on Birdvox visit here.