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CASE (Cluster & Analyse Sound Events)

version 1.0.0 (2.21 MB) by Sebastian Schneider
A tool to evaluate bioacoustic studies easily and automatically

54 Downloads

Updated 01 Mar 2021

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By means of this tool it is possible to extract up to 44 features of an animal sound in different ways. In addition, the tool includes various clustering algorithms (community detection; affinity propagation; HDBSCAN and fuzzy clustering) as well as algorithms to detect similarities between signals (k-nearest-neighbor; jaccard; dynamic-time-warping) in order to effectively classify animal sounds. The tool uses a graphical user interface to allow the user to work with the software as easily and intuitively as possible.

The following algorithms were adopted:

Affinity Propagation:
Kaijun Wang (2021). Adaptive Affinity Propagation clustering (https://www.mathworks.com/matlabcentral/fileexchange/18244-adaptive-affinity-propagation-clustering), MATLAB Central File Exchange. Retrieved March 1, 2021.

Community Detection:
Athanasios Kehagias (2021). Community Detection Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/45867-community-detection-toolbox), MATLAB Central File Exchange. Retrieved March 1, 2021.

HDBSCAN:
Jordan Sorokin (2021). Jorsorokin/HDBSCAN (https://github.com/Jorsorokin/HDBSCAN), GitHub. Retrieved March 1, 2021.

NMI:
Mo Chen (2021). Normalized Mutual Information (https://www.mathworks.com/matlabcentral/fileexchange/29047-normalized-mutual-information), MATLAB Central File Exchange. Retrieved March 1, 2021.

t-SNE:
Laurens van der Maaten & Geoffrey Hinton
https://lvdmaaten.github.io/tsne/

Cite As

Sebastian Schneider (2021). CASE (Cluster & Analyse Sound Events) (https://www.mathworks.com/matlabcentral/fileexchange/88039-case-cluster-analyse-sound-events), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with R2020a and later releases
Platform Compatibility
Windows macOS Linux

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CASE(Cluster_and_Analyse_Sound_Events)

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Algorithms

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Auxiliary

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/ClusterValidity

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Cluster_Number

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Evaluation

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Experiments

CASE(Cluster_and_Analyse_Sound_Events)/Community_detection/ComDetTBv090/Graphs

CASE(Cluster_and_Analyse_Sound_Events)/HDBSCAN/source

CASE(Cluster_and_Analyse_Sound_Events)/HDBSCAN/source/functions

CASE(Cluster_and_Analyse_Sound_Events)/ap_cluster

CASE(Cluster_and_Analyse_Sound_Events)/nmi

CASE(Cluster_and_Analyse_Sound_Events)/t-SNE