A repo designed to convert audio-based "weak" labels to "strong" intraclip labels. Provides a pipeline to compare automated moment-to-moment labels to human labels. Methods range from DSP based foreground-background separation, cross-correlation based template matching, as well as bird presence sound event detection deep learning models!
audio python training template-matching machine-learning natural-language-processing automation deep-learning neural-network python3 sound-processing birdsong object-detection sed foreground-detection bird-species-classification bioacoustics bird-audio-clips moment-labels human-labels
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Updated
Nov 22, 2024 - Jupyter Notebook