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[Analysis of bioacoustic recordings] #bio #raven #bioacoustic #opensoundscape
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analysis-of-bioacoustic-recordings.md

Analysis of Bioacoustic Recordings

Just a collection of links related to the "analysis of bioacoustic recordings".

It is a wide field and requires knowledge in signal processing, statsitical analysis, possibly machine learning (e.g. random forest).

There are some stand-alone application like "Raven Sound Analysis" and OpenSoundscape or extensions to standard statistical software R. Many librarys and tools are written in Python. Just have a look at the link below to see how many differnt application, tools, and approaches exist:

Background

Biodiversity monitoring has become a critical task for governments and ecological research agencies for reducing significant loss of animal species. Existing monitoring methods are time-intensive and techniques such as tagging are also invasive and may adversely affect animals. Bioacoustics based monitoring is becoming an increasingly prominent non-invasive method, involving the passive recording of animal sounds.

Published Papers

Just some papers that came up while I was looking into "analysis of bioacoustic recordings".

Identification of potential signature whistles from free‑ranging common dolphins (Delphinus delphis) in South Africa:

Spatial orientation of different frequencies within the echolocation beam of a Tursiops truncatus and Pseudorca crassidens:

THE IMPORTANCE OF BIOACOUSTICS FOR DOLPHIN WELFARE: SOUNDSCAPE CHARACTERIZATION WITH IMPLICATIONS FOR MANAGEMENT

Applications

Raven Sound Analysis

Raven provides very powerful tools for the analysis of (animal) sounds.

Rraven: Connecting R and Raven Sound Analysis Software

R can simplify the automatization of complex routines of analyses. Furthermore, R packages as warbleR, seewave and monitoR (among others) provide additional methods of analysis, working as a perfect complement for those found in Raven. Hence, bridging these applications can largely expand the bioacoustician’s toolkit.

R and bioacoustic analysis

R is the program for statistical analysis

OpenSoundscape

OpenSoundscape is free and open source software for the analysis of bioacoustic recordings. Its main goals are to allow users to train their own custom species classification models using a variety of frameworks, including convolutional neural networks, and to use trained models to predict whether species are present in field recordings.

Sonic Visualiser

Sonic Visualiser is a free, open-source application for Windows, Linux, and Mac, designed to be the first program you reach for when want to study a music recording closely. It's designed for musicologists, archivists, signal-processing researchers, and anyone else looking for a friendly way to look at what lies inside the audio file

Luscinia

Luscinia provides a flexible, fast and reliable way to semi-automatically measure bioacoustic signals. It measures 15 acoustic parameters as contours and hierarchical information about how complex signals are structured.

Other libraries and toolkits

SoundSort (AIPAM working name) is inpsired from a google experiment which demonstrated that bird sounds could be clustered very effectively using t-SNE:

Species-specific audio detection: a comparison of three template-based detection algorithms using random forests:

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