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Found 4 papers, 2 papers with code
LanSER: Language-Model Supported Speech Emotion Recognition
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.
Multitask vocal burst modeling with ResNets and pre-trained paralinguistic Conformers
This technical report presents the modeling approaches used in our submission to the ICML Expressive Vocalizations Workshop & Competition multitask track (ExVo-MultiTask).
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
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.
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task.
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