How to find a Morepork

In a previous blog (https://www.2040.co.nz/blogs/news/first-morepork-automatically-identified), you may have read about how I started down the road of automatically detecting morepork calls. Since then I’ve made some further progress and thought I’d share the journey so far with you

Bring the bird music back across New Zealand part of Smart Hamilton Smart Space

Every day, all around New Zealand, the dawn chorus tells us that our birdlife is one of our greatest treasures. Yet, New Zealand’s native birds are under threat from introduced predators such as possums, rats and stoats. How can modern information technology help to solve this problem

CacophonyViz: Visualisation of Birdsong Derived Ecological Health Indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

The Cacophony Project on Maungatautari

The Cacophony Project has arrived at Sanctuary Mountain Maungatautari and has been making regular audio recordings at one of the high points in the sanctuary since October 2018. The project aims to greatly improve the ability to eliminate pest predators throughout New Zealand and monitor the effects on bird life that this brings. It is well known that eliminating the last few pests using traditional techniques is difficult. The Cacophony Project envisages that this can be overcome by using lures such as sound and light to attract the last of these pests to one of numerous locations where they can be automatically identified using thermal cameras and artificial intelligence before beginning killed in a safe and humane manner

Is that what they said? An automated reference finder

This work investigates the feasibility of using freely available online resources to create an application that can automatically discover and display original source articles that a student cites and references. A prototype application was created that used CiteSeerExtractor to extract reference details from the student work, and then used Crossref.org to return web page addresses of the original journal articles or abstracts. Initial results successfully demonstrate that the idea is effective. It is concluded that further development would result in a useful tool for assisting in the marking of student work

Bring the bird music back across New Zealand part of Smart Hamilton Smart Space

Every day, all around New Zealand, the dawn chorus tells us that our birdlife is one of our greatest treasures. Yet, New Zealand’s native birds are under threat from introduced predators such as possums, rats and stoats. How can modern information technology help to solve this problem

Cacophonometer setup instructions

1. Introduction **** The current version (1.2) of the software can ‘hang’ for about 90 seconds when it starts up (it is testing if it can turn flight mode on/off). Please just give it time to do its thing. – working on a fix ***** The Cacophonometer consists of an Android App, Android phone and possibly an external microphone that together make regular audio recordings that can be uploaded to the Cacophony server for analysis. How you setup your Cacophonometer will depend on your particular scenario including: • Power supply - Mains power or solar panel? • Internet connection (Wifi, Mobile/SIM, none)? • Phone left in single location, or you are carrying it around with you (on a bush walk)? • Normal or test setup? • Using remote control software (AirDroid)

Part of 'AI to protect NZ birds': Bird classification open source contributers

The Cacophony Project has been bringing digital technology to the fight for New Zealand native birds. They are developing a set of technologies that will be deployed throughout New Zealand. Their technology will: - Lure invasive predators with sound and light - Observe predators using a thermal camera - Identify predators automatically using machine learning algorithms - Eliminate positively identified predators - Monitor the bird song over time to measure the impac

Analysis of morepork vocalizations recorded using a permanently located mobile phone

The purpose of this work included the annotation of audio recordings of bird vocalizations to be used to train a machine learning algorithm to automatically detect bird calls. In addition, this work was intended to demonstrate the ability of The Cacophony Project’s mobile phone based ‘Bird Monitor’ for on-going monitoring of bird vocalizations.This work is important because it forms part of The Cacophony Project’s strategy to provide a low cost and robust means of collecting bird vocalization information to help determine the effectiveness of pest control activities. The main results show that the Bird Monitor does reliably capture bird calls over an extended period and can be used to create many annotated recordings from a real situation. It is concluded that the approach of choosing the distinct call of the Morepork as an entry into the area of automatic bird call counting was valid

An investigation and comparison of speech recognition software for determining if bird song recordings contain legible human voices

The purpose of this work was to test the effectiveness of using readily available speech recognition API services to determine if recordings of bird song had inadvertently recorded human voices. A mobile phone was used to record a human speaking at increasing distances from the phone in an outside setting with bird song occurring in the background. One of the services was trained with sample recordings nd each service was compared for their ability to return recognized words. The services from Google and IBM performed similarly and the Microsoft service, that allowed training, performed slightly better. However, all three services failed to perform at a level that would enable recordings with recognizable human speech to be deleted in order to maintain full privacy protection