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Wednesday August 16, 2017

Recognising birdsong with artificial intelligence Researcher Victor Anton (right) and NEC’s artificial intelligence expert Paul Mathews. PHOTO: Supplied

New Zealand’s endangered native birds will sing a few extra notes when they hear artificial intelligence has joined the fight to increase their numbers. Victoria University of Wellington researchers are using ‘machine-learning’ software – a type of artificial intelligence – to analyse 25,000 hours of birdsong audio, saving tens of thousands of hours of listening time in a bid to uncover more effective forms of conservation. The technology popularly associated with driverless cars is helping researchers Victor Anton, Heiko Wittmer, and Stephen Hartley to analyse birdsong audio collected for a three-year study of currently threatened species the Hihi (Stitchbird), Tieke (Saddleback), and Kakariki (Red-crowned parakeet). Victor and his team have recorded tens of thousands of hours of birdsong using acoustic sensors at 50 locations in and around Zealandia – Wellington’s 225-hectare eco-sanctuary. Identifying the location and number of different bird calls in the audio will provide the data for Victor’s PhD thesis, which aims to identify factors influencing numbers of

threatened birds outside the eco-sanctuary. However, the prospect of sitting down to analyse so much audio threatened to overwhelm the researchers. So they called in NEC New Zealand to develop birdsong recognition technology to do the job faster and more accurately. “It’s difficult to recognise and count bird calls using audio recorded in a city – never mind the sheer number of hours of listening,” Victor said. “It’s not like we’re replacing unskilled labour – even experts sometimes struggle to identify the species of bird that made a call on this audio.” Using deep neural network software originally developed by Google engineers, NEC’s system learns to recognise different bird calls, effectively measuring the activity of each bird species at specific times and locations. Victor’s thesis will inform local councils and conservation organisations about effective management strategies for threatened wildlife in New Zealand urban areas. “Technology will ensure our conservation efforts focus in the right areas,” he said. “The prosperity of our endangered species


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Independent Herald 16-08-17  

Independent Herald 16-08-17

Independent Herald 16-08-17  

Independent Herald 16-08-17