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Welcome to the wiki for my approach on auto-ID of simply structured bird calls!

PROBLEM DESCRIPTION

We use a set of 12 high quality audio recorders microSoundRecorder to record bird vocalizations for species identification and mapping. This field recording effort is aimed at highly endangered, sometimes cryptic bird species, often vocalizing at night. For this WIKI, we describe the process with the example of the Eurasian Pygmy owl Glaucidium passerinum

If you record bird vocals for a week or two with 10 to 20 recorders, you will probably have a nice spatially distributed dataset, BUT you will also have a whole hard disk filled with one hundred or even more gigabytes of WAV recordings. No one will ever have the time to listen to all these recordings in order to identify the birds (unless you also have access to the working power of one hundred cheap, well trained and really keen students . . .). So there is a strong need for an automated method to identify the bird of target in all your recordings from the field. Katz (2015) and Katz et al. (2016a,b) described a simple, but quite effective way of doing this with the statistical software R and the library monitoR.

AIMS

• provide R code to set up a simple system that can automatically assign reliable ID scores for one selected target bird species to each WAV file recording made in the field. The system should be able to do batch processing, thus process large numbers of WAV files (in a folder on a hard disk for example), without needing manipulation from the user. The CPU time needed to assign the ID scores should not be higher than one tenth of the time needed to listen to the files directly :-)

ANALYSIS STEPS

• Training the system, so that it can identify the bird call in the recordings
• Classify your recording with the trained system
• Evaluate the quality of the Classifier by AUC evaluation

For detailed descriptions of those steps click on the links on the right side