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A Fully Automated, PC-based, Wildlife Monitoring and Survey System Neil J Boucher SoundID, Australia Michihiro Jinnai Nagoya University, Japan Biodiversity.

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Presentation on theme: "A Fully Automated, PC-based, Wildlife Monitoring and Survey System Neil J Boucher SoundID, Australia Michihiro Jinnai Nagoya University, Japan Biodiversity."— Presentation transcript:

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2 A Fully Automated, PC-based, Wildlife Monitoring and Survey System Neil J Boucher SoundID, Australia Michihiro Jinnai Nagoya University, Japan Biodiversity Technologies Symposium Oxford September 2012

3 What are these Calls? ? ? ? ?

4 And they are: Parrot Humpback Whale Mydau Bat

5 Harmonics In the real world, harmonics are mostly generated by distortion. In engineering we take great pains to avoid them. Harmonics have few uses (outside of music) and are mostly undesirable.

6 Harmonics in Bio-Acoustics These are mostly artefacts of the FFT (also known as the Harmonic Transform). They are sometimes the result of faulty/poor quality recording equipment. Occasionally animals actually produce harmonics.

7 Harmonics?

8 Why waste Energy? Were the whale to actually generate all those harmonics (with high frequencies and high propagation losses), it would be a very inefficient way to communicate. Additionally the sound of the whale would vary noticeably with distance (less high frequencies at distance).

9 Modulation

10 Before and After

11 Spectra of the Modulation Envelope of Whale Call

12 Recorder for up to 2 Months of Recording

13 Long-term Recorders

14 The Software

15 References The system works by comparing a library of WAV files (stored as mathematical images of their LPC spectrogram) with the spectrograms of the target sound.

16 LPC Transform Image of Kookaburra

17 LPC Transform of Rosella

18 Compare the Patterns as Images

19 Measure the Similarity using GD (here GD=10.80)

20 Geometric Distance It is an angle between two vectors (measured in degrees). For field recordings a distance of 6 degrees or less implies similarity of the sounds. Concept was developed by Jinnai. It measures the similarity of two sounds!

21 Determine a Similarity Value (GD) Typically we would use GD<=6.00 for similar matching call types. GD is “sort of” logarithmic, so calls with a GD of 6.00 are “roughly” 10 x more similar than those with a GD of A GD of is a VERY dis-similar distance.

22 Dawn Chorus List Australian Crow (Corvus spp.) Pied Currawong (Strepera graculina) Eastern Whipbird (Psophodes olvaceus) Grey Shrike-thrush (Colluricincla harmonica) Guineafowl (Numida spp.) Kookaburra (Dacelo spp.) Lewin’s Honeyeater (Meliphaga lewinii) Magpie (Gymnorhina tibicen) Noisy Miner (Manorina melanocephala) Pale-headed Rosella (Platycercus adscitus) Pied Butcherbird (Cracticus nigrogularis) Spur-winged Plover (Vanellus spp.) Rainbow Lorikeet (Trichoglossus haematodus) Eastern Sedgefrog (Litoria fallax)

23 Results from 1 Hour and 8 minutes of Dawn Chorus

24 Capabilities >100,000 comparisons per second Can analyse a whole HDD in a single run Can have any number of different species being searched for at the same time Accuracy greater than human expert Real-time recognition is possible Can handle terabytes of data in batch mode

25 PC Specs Any Windows PC will run the software Ideally one with a fast clock (>2.5 GHz) Screen size 1920 x 1080 is best

26 Time and Frequency Domain Image

27 Conclusions The time of the “better than human” sound identification has come. Very large acoustic surveys are now possible. The package has lots of new analysis tools. The system is available now at


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