  We present Burst2Vec, our multi-task learning approach to predict emotion,
age, and origin (i.e., native country/language) from vocal bursts. Burst2Vec
utilises pre-trained speech representations to capture acoustic information
from raw waveforms and incorporates the concept of model debiasing via
adversarial training. Our models achieve a relative 30 % performance gain over
baselines using pre-extracted features and score the highest amongst all
participants in the ICML ExVo 2022 Multi-Task Challenge.
