In total, NOAA provided about 15 years of audio, or 9.2 terabytes after decimation from 200 kHz to 10kHz. The data was recorded on devices called high-frequency acoustic recording packages, or HARPs ( Wiggins and Hildebrand, 2007 full text PDF). Since 2005, NOAA has collected recordings from ocean-bottom hydrophones at 12 sites in the Pacific Island region, a winter breeding and calving destination for certain populations of humpback whales. This has some advantages over ship-based visual surveys, including the ability to detect submerged animals, longer detection ranges and longer monitoring periods. Passive acoustic monitoring is the process of listening to marine mammals with underwater microphones called hydrophones, which can be used to record signals so that detection, classification, and localization tasks can be done offline. Passive Acoustic Monitoring and the NOAA HARP Dataset Green: sites with currently active recorders. That information will be a key ingredient for effective mitigation of anthropogenic impacts on humpback whales. Additionally, because the dataset spans a large period of time, knowing when and where humpback whales are calling will provide information on whether or not the animals have changed their distribution over the years, especially in relation to increasing human ocean activity. This is especially important in remote, uninhabited islands, about which scientists have had no information until now. The results of this research provide new and important information about humpback whale presence, seasonality, daily calling behavior, and population structure. National Oceanic and Atmospheric Administration (NOAA), we developed algorithms to identify humpback whale calls in 15 years of underwater recordings from a number of locations in the Pacific. Recently, we’ve become increasingly aware that many conservation organizations were collecting large quantities of acoustic data, and wondered whether it might be possible to apply these same technologies to that data in order to assist wildlife monitoring and conservation.Īs part of our AI for Social Good program, and in partnership with the Pacific Islands Fisheries Science Center of the U.S.
Furthermore, we have published the AudioSet evaluation set and open-sourced some model code in order to further spur research in the community. Over the last several years, Google AI Perception teams have developed techniques for audio event analysis that have been applied on YouTube for non-speech captions, video categorizations, and indexing. Posted by Matt Harvey, Software Engineer, Google AI Perception
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