no code implementations • 7 Sep 2023 • Taesik Gong, Josh Belanich, Krishna Somandepalli, Arsha Nagrani, Brian Eoff, Brendan Jou
Speech emotion recognition (SER) models typically rely on costly human-labeled data for training, making scaling methods to large speech datasets and nuanced emotion taxonomies difficult.
no code implementations • 24 Jun 2022 • Josh Belanich, Krishna Somandepalli, Brian Eoff, Brendan Jou
This technical report presents the modeling approaches used in our submission to the ICML Expressive Vocalizations Workshop & Competition multitask track (ExVo-MultiTask).
1 code implementation • ICLR 2022 • Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard
Explaining deep learning model inferences is a promising venue for scientific understanding, improving safety, uncovering hidden biases, evaluating fairness, and beyond, as argued by many scholars.
1 code implementation • 20 Sep 2019 • Asma Ghandeharioun, Brian Eoff, Brendan Jou, Rosalind W. Picard
Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task.