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
Jul 15, 2024 - Jupyter Notebook