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Models/M2D-CLAP/0.7

M2D-CLAP/0.7

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 ClassificationonESC-50
    Accuracy (5-fold)· uses extra data· 2024-06-04
    97.4
    best: 99.1 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032
  • Audio ClassificationonESC-50
    Top-1 Accuracy· uses extra data· 2024-06-04
    97.4
    best: 99.1 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032
  • Audio ClassificationonAudioSet
    Test mAP· 2024-06-04
    0.485
    best: 0.558 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032

Methodology3 results

  • ClassificationonESC-50
    Accuracy (5-fold)· uses extra data· 2024-06-04
    97.4
    best: 99.1 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032
  • ClassificationonESC-50
    Top-1 Accuracy· uses extra data· 2024-06-04
    97.4
    best: 99.1 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032
  • ClassificationonAudioSet
    Test mAP· 2024-06-04
    0.485
    best: 0.558 (OmniVec2)
    M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language RepresentationarXiv:2406.02032