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Models/Audio-CLAP

Audio-CLAP

Reported on 6 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Audio3 results

Audio ClassificationonICBHI Respiratory Sound Database
ICBHI Score· 2024-06-10
62.56
best: 65.53 (ADD)
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786
Audio ClassificationonICBHI Respiratory Sound Database
Sensitivity· 2024-06-10
44.67
best: 48.21 (BEATs (CE))
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786
Audio ClassificationonICBHI Respiratory Sound Database
Specificity· 2024-06-10
80.85
best: 85.13 (ADD)
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786

Methodology3 results

ClassificationonICBHI Respiratory Sound Database
ICBHI Score· 2024-06-10
62.56
best: 65.53 (ADD)
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786
ClassificationonICBHI Respiratory Sound Database
Sensitivity· 2024-06-10
44.67
best: 48.21 (BEATs (CE))
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786
ClassificationonICBHI Respiratory Sound Database
Specificity· 2024-06-10
80.85
best: 85.13 (ADD)
BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classification arXiv:2406.06786