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This package includes the raw data for a subset of the Hume Vocal Burst (Hume-VB) dataset used for the ExVo 2022 Competition. The competition is now over, please fill out this form to request access to the full Hume VB dataset. More information on the competition and dataset can be found in the competition white paper. -- This dataset contains 59,201 audio recordings of vocal bursts from 1,702 speakers, from 4 cultures, the U.S.A, South Africa, China, and Venezuela, ranging in age from 20 to 39.5 years old. The total duration of data in this version of Hume-VB is 36 Hours (Mean: 02.23 sec). A subset of 10 emotional intensity labels is also available. Data has been partitioned into equal training, validation, and test sets, and the test set is blind. Emotion Labels: Awe, Excitement, Amusement, Awkwardness, Fear, Horror, Distress, Triumph, Sadness, Surprise
machine learning, affective computing, vocal bursts
machine learning, affective computing, vocal bursts
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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