To that end, we tailor the AudioSet dataset (Gemmeke et al., 2017) that comprises 1,789,621 human-labeled 10 second YouTube excerpts with an ontology of 527 audio event categories.
an immediate collection of captions from these audios pose several difficulties: (i) too many audio clips, (ii) inconsistent level of abstraction among the classes, (iii) distribution bias of some labels and (iv) noisy labels that are only noticeable from visual cues.