Zero-Shot Respiratory Sound Classification through LLM-Augmented Audio-Text Alignment
This work proposes a framework that aligns self-supervised respiratory encoders with medical terminology in a shared latent space turning them into a zero-shot-capable foundation model, and uses a medical LLM to synthesize structured reports from metadata, creating dense semantic anchors for contrastive learning.
Mustafa Talha İlerisoy, Hung Manh Pham, Mathias Funk et al.
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