2020

FSD50K: An Open Dataset of Human-Labeled Sound Events

Fonseca, Eduardo, Favory, Xavier, Pons, Jordi et al.

Understand

Most existing datasets for sound event recognition (SER) are relatively small and/or domain-specific, with the exception of AudioSet, based on over 2M tracks from YouTube videos and encompassing over 500 sound classes.

However, AudioSet is not an open dataset as its official release consists of pre-computed audio features.
Downloading the original audio tracks can be problematic due to YouTube videos gradually disappearing and usage rights issues.
To provide an alternative benchmark dataset and thus foster SER research, we introduce FSD50K, an open dataset containing over 51k audio clips totalling over 100h of audio manually labeled using 200 classes drawn from the AudioSet Ontology.

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