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A pipeline for segmenting, clustering and visualizing Adelaide's warbler songs

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warbler

warbler is a pipeline for segmenting, clustering and visualizing Adelaide's warbler songs, which uses a dataset from Dr. David Logue of The Birdsong Lab. This pipeline uses UMAP to perform dimensionality reduction, and HDBSCAN and Fuzzy C-Means for clustering. We also developed avs for the purpose of excluding noise from our dataset.

This research is motivated by the repositories of Dr. Tim Sainburg (AVGN and vocalization segmentation) and Dr. Mara Thomas (UMAP Tutorial).

UMAP and Fuzzy C-Means Clustering

An animation depicting the dimensionality reduction and Fuzzy C-Means clustering of a Adelaide's warbler dataset

The dimensionality reduction and Fuzzy C-Means clustering of a Adelaide's warbler dataset

UMAP and HDBSCAN

An animation depicting the dimensionality reduction and HDBSCAN clustering of a Adelaide's warbler dataset

The dimensionality reduction and HDBSCAN clustering of a Adelaide's warbler dataset

Prerequisites

Windows

Linux (Debian)

sudo apt install graphviz graphviz-dev
sudo apt install ffmpeg

Setup

pyenv

pyenv install 3.11.2
pyenv local 3.11.2

Virtual Environment

python -m venv venv

Windows

"venv/Scripts/activate"

Unix

source venv/bin/activate

Packages

pip install -U -r requirements.txt && pip install -U -r local.txt

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A pipeline for segmenting, clustering and visualizing Adelaide's warbler songs

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