MUNIN: Metric-learning Unit for Non-invasive Individual Naming
Lightweight few-shot learning for acoustic individual identification in birds. A ResNet18 encoder trained from scratch on mel spectrograms using episodic prototypical learning.
Key Result
MUNIN (11M parameters, 512-d embeddings) achieves parity with BirdNET (pretrained on 6,000+ species, 1024-d) for individual bird identification:
Setting
MUNIN
BirdNET
Perch
1-shot
85.0%
81.4%
80.4%
3-shot
89.9%
91.5%
90.8%
5-shot
93.9%
94.1%
92.8%
TOST equivalence at 5-shot within +/-2pp margin (p=0.0013). Evaluated on 9 held-out individuals across 3 species.
Checkpoints
File
Description
MUNIN flagship -- best 5-shot model (93.9%)
3-shot variant (89.9%)
1-shot variant (85.0%, leads BirdNET)
Usage
Input Format
Mono audio at 22050 Hz
Mel spectrogram: 128 bins, 1.5s clips (65 frames)
Shape:
Training
Episodic prototypical learning (5-way 5-shot)
27 training individuals across 3 species (cockatoo, penguin, little owl)
50 epochs, 200 episodes/epoch, cosine annealing LR
