ResearchLocalisation of bird calls in NZ bush
Have you ever spotted kiwi birds in NZ bush? Can you imagine how many of them are living in a forest? It is actually quite rare that you come across birds like kiwis because of their declining population and nocturnal lifestyle. Therefore it is a quite challenging task for the rangers and researchers to study the ecology of such birds without actually staying in a forest for weeks and months. The DOC (Department of Conservation) has been attempting to study ecology of birds by their calls recorded in forests, however so far this has been done completely manually (hiring people and get them to literally “listen and identify” bird calls) which is not cost effective and the results can also be inaccurate. Recently the DOC is working with a group of researchers around NZ (known as AviaNZ) to develop an automated system to identify bird calls as well as measuring abundance of species. The head of CAL Yusuke Hioka is a part of the group in charge of extracting various acoustic information from the recordings. In this project we focus on localising bird calls (i.e. extracting “location” of birds such as direction and distance from recordings) using digital signal processing with microphone arrays (i.e. array of more than one microphones).
Publications/conference presentations relevant to this research
- C. Jiang, Y. Hioka, and S. Marsland. Investigating the feasibility ofusing direct-to-reverberant energy ratio to estimate birdcall distances.InAcoustical Society of NZ Conference, June 2021.
B. Ollivier, A. Pepperell, Z. Halstead, and Y. Hioka. Noise robust bird call localisation using the generalised cross-correlation in the wavelet domain. Journal of the Acoustical Society of America, 146:4650–4663, 2019.
A. Pepperell, Z. Halstead, B. Ollivier, and Y. Hioka. Performance of sound source localisation for bird calls in native new zealand bush. New Zealand Acoustics, 32(2):15–24, 2019.
C. Gray and Y. Hioka. Direction of arrival estimation of kiwi call in noisy and reverberant bush. In 2014 IEEE Sensors Applications Symposium (SAS 2014), Feb 2014.