A Santa Cruz, California based company is using big data and deep learning to improve conservation efforts. California birdwatchers can go a lifetime without seeing the globally endangered marbled murelett bird and with now with remote acoustic sensors and deep learning, biologists are now able to analyze the audio of the bird, and keep better track the populations of species that were previously hard to monitor.
In a recent article, the CEO of Conservation Metrics mentioned, “we need to improve conservation by improving wildlife monitoring. Counting plants and animals is really tricky business.” And they are doing so with the help of TITAN GPUs.
The company created spectrograms of bird calls compiled from acoustic data they gathered and is converted into a visual representation — time runs along the x-axis, audio frequency along the y-axis — and then an algorithm searches for patterns to isolate specific bird calls. In the soundscape, many different species are making noise at once, but the computer has identified a marbled murrelet call within the clip. It’s the upside-down horseshoe pattern running along the lower third:
To listen to the audio and to read the complete interview, visit the FiveThirtyEight website >>
AI-Generated Summary
- Conservation Metrics applies deep learning and acoustic sensors to monitor endangered marbled murrelet populations that are difficult to track by traditional methods.
- The company converts bird-call audio into spectrograms and uses pattern-recognition algorithms to isolate specific species calls within complex soundscapes.
- Processing is accelerated with TITAN GPUs to handle the computational demands of the analysis.
Next Step
- Read the FiveThirtyEight article to hear the audio and see the full interview.
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