Codesota · Computer Vision · Few-Shot Image Classification · DESEDTasks/Computer Vision/Few-Shot Image Classification
Few-Shot Image Classification · benchmark dataset · EN

DESED.

DESED dataset is a dataset designed to recognize sound event classes in domestic environments. This dataset is designed to be used for sound event detection (SED, recognize events with their time boundaries) but it can also be used for audio tagging (AT, indicate presence of an event in an audio file). For now, the dataset is composed of 10 event classes to recognize in 10 second audio files. Classes: Alarm/bell/ringing, Blender, Cat, Dog, Dishes, Electric shaver/toothbrush, Frying, Running water, Speech, Vacuum cleaner.

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  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies
DESED — Few-Shot Image Classification benchmark · Codesota | CodeSOTA