The dataset consists of the features associated with 402 5-second sound samples. The 402 sounds range from easily identifiable everyday sounds to intentionally obscured artificial ones. The dataset aims to lower the barrier for the study of aural phenomenology as the largest available audio dataset to include an analysis of causal attribution. Each sample has been annotated with crowd-sourced descriptions, as well as familiarity, imageability, arousal, and valence ratings.

Source: https://github.com/mitmedialab/HCU400

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